1 DISTINCT PATTERN OF WALKING RECOVERY FOLLOWING THERAPEUTIC INTERVENTIONS POST STROKE: RESPONDERS VS. NON RESPONDERS By SHILPA PATIL SHARMA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PA RTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2013
2 2013 Shilpa Patil Sharma
3 To my f amily, for all their support and encouragement
4 ACKNOWLEDGMENTS I would like to thank everyone who has provided their help and support in one way or the other through this journey of getting my PhD. First and foremost I would like to thank my mentor Dr. Carolynn Patten for guiding and supporting me through my dissertat ion work and for introducing and familiarizing me to the wonderful world of research. I would like to thank all the members of my diss ertation committee, Dr. Rosenbe k, Dr. Fregly, Dr. Hass and Dr. Presnell for sharing their valuable time and years of exper ience and wisdom with me. I would like to thank each and every member of the pattenlab family: Dorian, Dave, Ginny, Manuela, Martina, Theresa John, Jennifer, Emily and Albina for making me part of their team. I would like to thank all the engineers Scott Nick and Theresa for helping me with the data analysis over the years and also to other members of the Brain Rehabilitation Research Center, Carolyn and Helen for all their help. I would also like to give a big thanks to my friend and colleagues Neha Lod ha and Bhavana Raja for the enlightening and productive discussions and for all their help. Special thanks to all the people who are recovering from their stroke and participated in these studies. Last and not the least I would like to thank my friends an d family for believing in me and for their constant moral support and encouragement. I would especially like to thank my mom and dad for their unquestionable trust in my ability to undertake this journey and for all the sacrifices they have made over the y ears to help me achieve my goal. I would also like to thank my br other and best friend Abhijeet for coming to the US just to be there for me and support me. Special thanks go to my husband Anil for being my constant pillar of support, making me laugh when I was down and helping me in any way possible. In the end I would like to thank the person I love most, my daughter
5 Kenisha for just being a part of my life and bestowing me with all her lo ve and trust and making my journey so much more worthwhile and plea sant.
6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 10 LIST OF FIGURES ................................ ................................ ................................ ........ 11 ABSTRACT ................................ ................................ ................................ ................... 13 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 15 1.1. Significance of the Problem ................................ ................................ ............. 15 1.2. Neuromotor Con trol of Normal Walking ................................ ........................... 16 1.2.1. Spinal Pattern Generators ................................ ................................ ...... 17 1.2.2. Descending Influences ................................ ................................ ........... 18 1.2.3. Sensory Feedback ................................ ................................ .................. 18 1.2.4. Muscle Activity Pattern during Normal Walking ................................ ...... 19 1.3. Characteri stics of Gait following Stroke ................................ ........................... 21 1.3.1. Spatiotemporal Parameters ................................ ................................ .... 21 1.3.2. Kinematic Parameters ................................ ................................ ............ 22 1.3.3. Kinetic Parameters ................................ ................................ ................. 23 1.4. Underlying Neuro musculo skeletal Impairments ................................ ............. 25 1.4.1. W eakness ................................ ................................ ............................... 25 1.4.2. Abnormal Muscle Synergies/ Abnormal Muscle Activation Pattern ........ 26 1.4.3. Proprioception ................................ ................................ ........................ 27 1.5. Current Therapeutic Approaches ................................ ................................ ..... 29 1.5.1 Strength Training ................................ ................................ ..................... 29 1.5.2. Locomotor T raining ................................ ................................ ................. 31 1.5.3. Speed Training ................................ ................................ ....................... 33 1.6. Recovery of Walking Function in Stroke Hemiparesis ................................ ..... 35 1.7. Responders vs. Non responders ................................ ................................ ..... 39 2 COMMON METHODS ................................ ................................ ............................ 42 2.1 Subjects ................................ ................................ ................................ ............ 42 2.1.1. Participants ................................ ................................ ............................. 42 2.1.2. Experimental Design ................................ ................................ .............. 43 2.1.3. Randomization and Blinding ................................ ................................ ... 43 2.1.4. Identifying Responders vs. Non Responders ................................ ......... 44 2.2. Measures ................................ ................................ ................................ ......... 45 2.2.1. Clinical Assessments ................................ ................................ .............. 46 18.104.22.168. Lower extremity Fugl Meyer motor assessment ........................... 46 22.214.171.124. Lower extremity Fugl Mey er synergy sub score ............................ 47
7 126.96.36.199. European stroke scale ................................ ................................ .. 47 188.8.131.52. Six minute walk test ................................ ................................ ...... 48 184.108.40.206. Timed up and go ................................ ................................ ........... 48 220.127.116.11. Berg balance scale ................................ ................................ ........ 48 18.104.22.168. Functional independence measure ................................ ............... 49 2.2.2. Three Dimensional Motion Analysis ................................ ....................... 50 22.214.171.124. Data collection ................................ ................................ .............. 50 126.96.36.199. Data reduction ................................ ................................ ............... 51 2.2.3. Strength ................................ ................................ ................................ .. 54 188.8.131.52. Data collection ................................ ................................ .............. 54 184.108.40.206. Data reduction ................................ ................................ ............... 55 2.3. Intervention ................................ ................................ ................................ ...... 56 2.3.1. Power Training ................................ ................................ ....................... 56 2.3.2. Gait Training ................................ ................................ ........................... 57 2.4 Statistical Analyses ................................ ................................ ........................... 58 2.4.1. Statistical analysis for Chapters 3, 4 a nd 5 ................................ ............. 58 2.4.2. Statistical analysis for Chapter 6 ................................ ............................ 59 3 CLINICAL CHARACTERISTICS: RESPONDERS VS. NON RESPONDERS ........ 65 3.1. Background ................................ ................................ ................................ ...... 65 3.2. Methods ................................ ................................ ................................ ........... 67 3.2.1. Participants ................................ ................................ ............................. 67 3.2.2. Experimental Design ................................ ................................ .............. 68 3.2.3. Intervention ................................ ................................ ............................. 68 220.127.116.11. Power training ................................ ................................ ............... 68 18.104.22.168. Gait training ................................ ................................ ................... 69 3.2.4. Measurements ................................ ................................ ........................ 70 22.214.171.124. Primary ou tcome measure. ................................ ........................... 71 126.96.36.199. Secondary outcome measures ................................ .................... 71 3.2.5. Data Analysis ................................ ................................ ......................... 72 3.3. Results ................................ ................................ ................................ ............. 73 3.3.1. Differential Effects of Training and Mode of Strength Training ............... 73 3.3.2. Identification of Responders and Non responders ................................ 74 3.3.3. Baseline Differences between Responders and Non responders .......... 74 3.3.4. Changes in Outc ome Measures: RES vs. NRES ................................ ... 75 188.8.131.52. Clinical assessments ................................ ................................ ..... 75 184.108.40.206. Spatiotemporal parameters ................................ ........................... 75 220.127.116.11. Isometric strength ................................ ................................ .......... 75 3.4. Discussion ................................ ................................ ................................ ....... 76 3.4.1. Differential Effects of Training a nd Mode of Strength Training ............... 76 3.4.2. Responders and Non responders ................................ ........................... 77 3.4.3. Baseline Differences between Responders and Non r esponders .......... 79 3.4.4. Changes in Clinical Outcome Measures: Responders vs. Non responders ................................ ................................ ................................ .... 80 4 BIOMECHANICAL PROFILE: RESPONDERS V S. NON RESPONDERS ............. 97
8 4.1. Background ................................ ................................ ................................ ...... 97 4.2. Methods ................................ ................................ ................................ ......... 100 4.2.1. Study Design ................................ ................................ ........................ 100 4.2.2. Participants ................................ ................................ ........................... 101 4.2.3. Intervention ................................ ................................ ........................... 101 4.2.4. Outcome Measures ................................ ................................ .............. 102 18.104.22.168. Data management ................................ ................................ ....... 103 4.2.5. Data Analysis ................................ ................................ ....................... 104 4.3. Results ................................ ................................ ................................ ........... 105 4.3.1. Baseline Differences between the Responders and the Non Responders ................................ ................................ ................................ 105 4.3.2. Changes from Pre Intervention to Post Intervention ............................. 106 22.214.171.124. Joint angles ................................ ................................ ................. 106 126.96.36.199. Internal joint moments ................................ ................................ 107 188.8.131.52. Joint powers ................................ ................................ ................ 108 4.4. Discussion ................................ ................................ ................................ ..... 109 4.4.1. Baseline Differences between the Responders and the Non Responders ................................ ................................ ................................ 109 4.4.2. Changes from Pre Intervention to Post Intervention ............................. 110 4.5. Limitations ................................ ................................ ................................ ...... 113 5 MECHANISM OF IMPROVEMENT: RESPONDERS VS. NON RESPONDERS 124 5.1. Background ................................ ................................ ................................ .... 124 5.2. Methods ................................ ................................ ................................ ......... 126 5.2.1. Data Collection ................................ ................................ ..................... 126 5.2.2. Data Reduction ................................ ................................ ..................... 127 5.2.3. Outcome Measures ................................ ................................ .............. 128 5.3. Results ................................ ................................ ................................ ........... 129 5.3.1. Baseline Difference between the Responders and the Non Responders ................................ ................................ ................................ 129 184.108.40.206. EMG ................................ ................................ ............................ 129 220.127.116.11. Ground reaction forces: ................................ ............................... 130 5.3.2. Changes from Pre Intervention to Post Intervention ............................. 130 18.104.22.168. EMG ................................ ................................ ............................ 130 22.214.171.124. Ground reaction forces: ................................ ............................... 130 5.4. Discussion ................................ ................................ ................................ ..... 131 6 KEY FACTORS PREDICTING RESPONDERS FOLLOWING INTERVENTION POST STROKE: A MULTIVARIATE ANALYSIS ................................ .................. 14 5 6.1. Background ................................ ................................ ................................ .... 145 6.2. Research Design and Methods ................................ ................................ ...... 147 6.2.1. Data Analysis ................................ ................................ ....................... 147 6.3. Results ................................ ................................ ................................ ........... 149 6.4. Discussion ................................ ................................ ................................ ..... 151
9 7 CONCLUSION ................................ ................................ ................................ ...... 154 A PPENDIX: OUTCOME MEASURE S ................................ ................................ ......... 157 LIST OF REFERENCES ................................ ................................ ............................. 161 BIOGRAPHICAL SKET CH ................................ ................................ .......................... 177
10 LIST OF TABLES Table page 2 1. Participant demographics and clinical characteristics ................................ ......... 60 3 1. Demographics for the whole cohort, responders, non responders, concentric and eccentric group. ................................ ................................ ........................... 82 3 2. Descriptive statistics for walking speed and changes in walking speed fo r the whole cohort and by group ................................ ................................ ................. 84 3 3. Descriptive statistics for spatiotemporal parameters and changes in spatiotemporal variables by group post intervention ................................ .......... 86 3 4. Descriptive statistics for isometric strength and changes in isometric strength by group post intervention ................................ ................................ .................. 87 3 5. Descriptive statistics for clinical s cores at baseline and following intervention. .. 88 4 1. Descriptive statistics for baseline kinematics and kinetics measure and changes in kinematics and kinetics variables from pre to post inte rvention by group and for speed matched controls ................................ ............................. 114 5 1. Descriptive statistics for the ground reaction force measures for responders and non responders pre intervention and post intervention ............................. 133 5 2. Descriptive statistics for percentage integrated EMG in each bin for RES and NRES at pre intervention and post intervention ................................ ............... 135 6 1. Shows the coefficients and threshold for the discriminant equations for full model and the model fitted on the 2 parts of the data set ................................ 153
11 LIST OF FIGURES Figure page 2 1. Consort diagram of participant progression through the trial. ............................. 62 2 2. P ositioning and the custom attachments for power training and strength testing. ................................ ................................ ................................ ................ 63 2 3. Exercise prescription showing the progression for the lower extremity power training. ................................ ................................ ................................ ............... 64 3 1. Consort diagram of particip ant progression through the trial .............................. 89 3 2. Exercise prescription showing the progression for the lower extremity power training. ................................ ................................ ................................ ............... 90 3 3. P ositioning and the custom attachments for power training and strength testing. ................................ ................................ ................................ ................ 91 3 4. Mean walking speed at baseline and following interventions and changes in walking speed followin g gait training for the whole cohort and responder, non responder, concentric and eccentric groups ................................ ................ 92 3 5. Mean value and changes in spatiotemporal parameters at baseline and following interve ntions for the whole cohort, responders, and non responders. ................................ ................................ ................................ ......... 93 3 6. Mean value and changes in strength measures for the paretic leg at baseline and following interventions for the whole cohor t, responders, and non responders. ................................ ................................ ................................ ......... 95 4 1. Consort diagram of participant progression through the trial ............................ 120 4 2. Represents base line differences between the RES and the NRES and between each group and their speed matched controls for joint angles and moments. ................................ ................................ ................................ .......... 121 4 3. Represents changes in select joint angles and momen ts from pre intervention to post intervention for both paretic and non paretic side of the RESs, NRESs and respective speed matched controls. ................................ .. 122 4 4. Represents the changes in select joint po wer from pre intervention to post intervention for both paretic and non paretic side for the RES and the NRES and respective speed matched controls. ................................ .......................... 123
12 5 1. Percentage integrated EMG activity in different bins over the gait cycle for paretic and non paretic side of non responders and speed matched controls both pre intervention and post intervention.. ................................ .................... 139 5 2. Percentage integrate d EMG activity in different bins over the gait cycle for paretic and non paretic side for responders and speed matched controls both pre intervention and post intervention.. ................................ ............................ 142
13 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DISTINCT PATTERN OF WALKING RECOVERY FOLLOWING THERAPEUTIC INTERVENTIONS POST STROKE: RESPONDERS VS. NON RES PONDERS By Shilpa Patil Sharma December 2013 Chair: Carolynn Patten Major: Rehabilitation Science Following a staged intervention with 5 weeks of power training followed by 3 weeks of gait training we identified 2 distinct groups of individual s based o n the improvement in their walking speed: responders and non responders. Ernst in his review on stroke rehabilitation in 1990 had expressed an urgent need to design well planned clinical trials aimed at finding the best treatment approach and discriminatin g potential responders. However, this issue has only rec ently been investigated. S troke is one of the most leading cause s of disability worldwide and leaves more than 67% of individuals who have walking impairment following stroke unable to achieve indepen dent walking Consequently, walking recovery is one of the most articulated goals in stroke rehabilitation Moreover a large clinical trial recently showed that only about 52% of individuals post subacute stroke improve their walking function following int ervention. Consequently, there is a n urgent need to understand why some individuals respond to treatment to a greater extent and how this information can be used in clinic s to the advantage of a clinician.
14 This dissertation informs us that individuals wh o respond have better lateral stabilization of their pelvis and are able to transfer weight from the paretic to the non paretic leg more efficiently at baseline. Moreover, they achieve improvement in their walking speed following treatment by using restora tion as well as compensation both proximally and distally whereas non responders use intra limb compensation by more proximal muscles and inter limb compensation by the non paretic leg. Finally, using a multivariate approach by a combination of Sure Indep endent Screening, Envelope model and Fischer Discriminant analysis we also developed a criteri on based on 8 key gait measures at baseline which could a priori identify the potential responders.
15 CHAPTER 1 INTRODUCTION 1.1. Significance of the Problem Appr oximately 795,000 people experience new or recurrent stroke each year. Stroke accounts for approximately 1 of every 18 deaths occurring in the United States. On average, someone in the United States has a stroke every 40 seconds. Althou gh, stroke death rat e fell 33.5% from 1996 2006, still in 2006 stroke was the third most is also among the fifteen leading conditions in US that cause functional disabilities limiting their activities in communi ty or home. 1 About 40 50% of individuals who survive stroke are reported to have physical disability, 2 4 walking disability being one of the major problems. Although, the majority of stroke survivors regain some ability to walk during the first six weeks post stroke, 40% still have severe motor impairments that restrict fun ctional walking to household ambulation. However, out of these individuals who achieve physical independence in walking, 60% will be limited in community ambulation. 5 Only a small percentage of these individuals are able to return to their pre stroke community status. 6 7 Stroke results in a multitude of sensorimotor impair ments including: spasticity, weakness, impaired selective motor control and proprioceptive deficits that result in gait dysfunction. Consequently walking in individuals with stroke is characterized by: slow walking speed, reduced cadence, stride length, lo nger stance phase on the unaffected side and reduced joint excursions 8 10 ; asymmetry in temporal, spatial, kinematic and kinetic gait variables 11 14 ; abnormal muscle activation patterns 15 16 and increased mechanical energetic and metabolic cost 17 18 Moreover, as impaired walking
16 contributes significantly to functional disability following stroke 19 improved mobility and restoration of walking is one of the most frequently articulated goals of stroke rehabilitation 6 20 21 Hence, one of the crucial components of stroke rehabilitation is the re storation of walking function to facilitate independent living. However, a recently conducted clinical trial of locomotor training shows that at 1 year after stroke only about 52% of individuals responded to rehabilitation by showing an improvement in walk ing function. 22 Hence, there is a need to understand the characteristics of individuals who Although, to understand mechanisms of walking recovery and characteristics of individuals who respond to therapeu tic intervention, it is first imperative to understand: normal walking and its neural control, the characteristic gait patterns following stroke and the motor dysfunctions resulting from stroke that contribute to these gait impairments. 1.2. Neuromotor Co ntrol of Normal Walking To understand the control of gait, it is often easier to examine gait with respect to the essential requirements of gait which include: forward progression, stability and adaptation, and the conditions that must be met during differ ent phases of gait (i.e., stance and swing) to meet these requirements. For example, during the support phase of gait horizontal forces are produced to move the body forward (Anterior posterior ground reaction force) and vertical forces are produced to sup port the body against gravity (VGRF). Control of normal walking is achieved through the integration of information at three levels: pattern generators at the spinal level, descending or supraspinal influences and sensory feedback and adaptation of gait.
17 1. 2.1. Spinal Pattern Generators The basic pattern for stepping is generated in the spinal cord, while fine control of walking involves various brain regions, including motor cortex, cerebellum and brain stem. 23 Locomotor patter n generators (LPGs) in the spinal cord are responsible for producing rhythmic patterned outputs which are shown to produce and coordinate locomotion. LPGs are networks of nerve cells producing specific, rhythmic movements such as walking without conscious effort and without the aid of peripheral afferent locomotor pattern generators. 24 These rhythmic movements are modified by supraspinal influences durin g complex demands of daily gait related activities. Although, most of the evidence for the presence of LPGs is based on animal studies (Grillner 1985, Rossignol 2000, Graham Brown 1911) there is indirect evidence to show that these also exist in humans. 25 Human infants exhibit a stepping pattern even before birth and this primitive ability continues throughout life to enhance mobility. 26 Spinal patter n generators are activated by non patterned and non specific descending drive from the higher brain centers and are capable of recruiting muscles in the correct sequence to obtain a coordinated walking pattern. Although, like animal quadrupedal walking, hu man walking is based on the integration of spinal pattern generators, sensory feedback and descending supraspinal influences. The LPG activity and its interaction with other central circuitries have been modified in various ways to meet the functional requ irements of human bipedal walking. 27
18 1.2.2. Descending Influences In humans, the activities of CPGs are much more dependent on supraspinal influences than in other species. Our knowledge regarding the control of walking by human cortex is still not develo ped completely. 27 Unlike other animals, such as the cat, in humans an intact motor cortex is considered a prerequisite for walking. 27 However, it has been shown that transmission of the command signal from the motor cortex to the spinal cord does not need to be transmitted directly through the corticospinal tract but may also be channeled through other pathways. 27 Recent studies using transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) show that primary motor cortex is i nvolved in controlling rhythmic movements. Several groups have demonstrated that the transmission in the corticospinal tract is greatly modulated during the walking cycle. 28 30 For example it has been shown that motor evoked potentials (MEPs) in the soleus as evoked by TMS, are large in the stance phase and absent in the swing phase. 28 30 Moreover, this modulation of MEPs is caused by changes in excitability of corticospinal cells with direct monosynaptic projections to the spinal interneurons. 29 When inhibited, these monosynaptic pathways depress the ongoing electromyography (EMG) activity in leg muscles during walking. 31 Hence, in humans, the motor cortex makes a significant contribution to the activation of the muscles throu gh the direct monosynaptic projections to the spinal motor neurons during locomotion. 1.2.3. Sensory F eedback Sensory feedback plays three crucial roles in the control of walking. Firstly, sensory feedback may help to drive the active motor neurons. Secon dly, it may contribute to corrective reflexes following sudden perturbations and lastly, sensory
19 feedback may provide essential error signals that inform the brain of differences between the intended movement and the movements already executed, which may b e used for updating of the future movements (i.e. motor learning) 27 The importance of sensory feedback to the motor neuronal drive during human walking is also demonstrated by experiments 32 in which ankle extensors of an individual walking on treadmill were suddenly unloaded at different times during the stance phase of walking. This perturbation was accompanied by significant drop in the EMG activity recorded from the active ankle plantarflexors showing that positive feedback from the active muscle contributes to the motor neuronal drive during walking. In addition, sensory feedback is also considered important for corrective reflexes. 1.2.4. Muscle Activity Pattern d uring Normal Walking Coordination of a number of different muscle activities at different joints is required for accomplishing the complex task of walking. In order to have the flexibilit y in walking pattern so that an individual can adapt to various surfaces and terrains, muscle activity at different joints is not coupled rigidly. Indeed, such coupling is restricted to motor units within the same mus cle and close synergists. This flexibil ity allows scaling of muscle activation patterns to ensure the correct movement trajectory. The resulting patterns represent integrated activity of spinal neuronal circuits, sensory feedback signals and descending supraspinal motor commands. 27 Hence, multi ple control systems at different levels of the central nervous system (CNS) contribute to generate this muscle activity, to ensure that it is optimally coordinated, to ensure that it is adjusted to the immediate environment, and to modify it when required. Although there is similarity in the muscle activation patterns between subjects and conditions, a
20 fundamental, underlying pattern exists. It is easier to understand the activity of muscles based on the biomechanical goals of the different phases of gait c ycle. Stance phase. During stance phase there are two main goals that need to be accomplished: i) maintain stability against the perturbation from impact during foot strike and ii) forward progression by generation of force to move the body forward into t he next step. Various muscle groups act to achieve the goal of stability. For example, knee extensors work eccentrically to control knee flexion during loading that is used to absorb the impact of foot strike w hile ankle dorsiflexors work eccentrically to control the movement of foot into plantarflexion on loading. In addition, extensor muscles at the hip, knee and ankle act to control the body from collapsing under the influence of gravity while hip extensors control the forward motion of the upper body. O n the other hand certain muscle groups work to achieve forward progression during walking. For example, concentric contraction of ankle plantarflexors (gastrocnemius and soleus) during late stance generates propulsive forces for forward progression of body Swing Phase. The major goal of muscle action in the swing phase is to reposition the limb for forward progression by accelerating the limb forward and toe clearance. Forward acceleration of the limb is initiated by knee extensors which start this movemen t, by acting concentrically in early swing and is followed by hip flexor activity during mid swing. During swing phase the knee extensors are no longer working and the leg swings through, much like a pendulum. At the end of swing knee flexors (hamstrings) act eccentrically to control the extension of knee and the forward rotation of thigh in preparation for foot placement for next heel strike, w hereas, toe clearance is accomplished as a result of overall shortening of the swing limb by flexion at hip, knee
21 and ankle joints. Hip flexion occurs as a result of quadriceps (i.e., rectus femoris) activity, while knee flexion is passive, occurring as a result of pendulum motion. Ankle dorsiflexion acts concentrically during swing to assist with toe clearance. 33 1.3. Characterist ics of Gait following Stroke 1.3.1 Spatiotemporal Parameters Asymmetry is a dominant characteristic of hemiparetic walking. 8 14 34 However, myriad variables have been used to quantify spatiotemporal asymmetry. Inconsistent reporting of important variables has limited our understanding of the underlying impair ments. Some studies report temporal parameters while others report spatial parameters with very few studies reporting both sets of variables in detail. Moreover, the dependency of these spatiotemporal characteristics on walking speed has to be considered f or accurate interpretations of these data. 35 Despite these complications, some general patterns have emerged. In terms of the temporal parameters, first, it has been reported that individuals with stroke spend significantly more time in stance phase on the non paretic leg than on the paretic leg. 8 36 Concomitantly, they spend significantly greater time in paretic swing phase. Secondly, it has been reported, alt hough inconsistently, that the initial double limb support (DLS) of the non paretic leg (i.e., when the paretic limb is in pre swing) is longer in duration than the initial paretic leg double support phase (i.e., when the paretic leg accepts weight during loading). 8 37 Some studies reported no significant difference between the two support phases although they did show that both paretic and the non paretic limb double support phases were longer than in controls. 36 Furthermore, spatial asymmetry has also been reported, as characterized by differences in the paretic and non paretic step lengths. However, while most studies
22 have reported longer paretic step length, some individuals exhibit asymmetry in the opposite direction. 38 39 A recent study by Balasubramanian showed that step length asymmetry is related to propulsive forc e generation and that individuals with poor paretic limb propulsion walk with relatively longer paretic steps. 40 1.3.2 Kinematic P arameters The kinematics of hemiparetic walking is altered in both legs relative to healthy walking. Major kinematic differences as compared to able bodied individuals were reported by Burdett and colleagues as: decreased hip flexio n in mid swing, exaggerated knee flexion at initial contact and reduced knee flexion at toe off and mid swing; increased ankle plantar flexion at initial contact and mid swing and less ankle plantar flexion at toe off. 41 The magnitude of these kinematic deviations has been shown to be related to the speed of walking. 15 42 43 Paretic hip motion becomes more abnormal during pre swing as self selected w alking speed declines, with hip flexion not occurring until toe off in severe cases, to hip flexion occurring at the midpoint of pre swing in moderate cases. 37 However, the timing of the non paretic hip flexion remains normal even in the slowest walkers. 37 Olney et al showed a similar dependence on gait speed for knee angular excursion. 8 Individuals were grouped into 3 categories of slow, medium and fast based on their average walking speed of 0.25, 0.41 and 0.63m/s, resp ectively. The maximum knee flexion of the affected limb during swing phase ranged from 38 degrees in the slow group to 48 degrees in the fast group, whereas on the unaffected side knee flexion was close to 64 degrees for the fast and medium groups and 54 degrees for the slowest. Similarly, knee flexion in stance phase showed a better pattern in fast walking (from 10
23 degrees knee flexion at initial contact smoothly transitioning to approach extension in late stance) as compared to slow walking (15 degrees k nee flexion at initial contact that prevailed even during late stance) individuals. 8 Other studies have also shown an 37 44 with increased ankle plantar flexion and knee hyperextension throughout stance, inadequate ankle dorsiflexion in pre swing and inadequate knee flexion in swing. Although the foot was predominantly in a pla ntar flexed position throughout most of the stance, in individuals with stroke, the peak paretic plantarflexion during pre swing was still less than those with normal walking. In fact, eight individuals with severe hemiparesis were found to have little or no plantar flexion in pre swing. 37 Hence it is evident that the kinematics is disturbed in the hemipareti c and exhibit asymmetry. 1.3.3 Kinetic P arameters In hemiparetic walking three different patterns of vertical ground reaction force (VGRF) are typically observed in the paretic limb: double peaked with early and late peaks similar to normal, one single p eak in mid stance, and a plateau with no peak that emerges with reduced walking speed. 45 The magnitude of vertical GRF is reduced in the paretic leg. 39 Similarly, anterior posterior GRFs (AP GRF) have been studied. AP GRF has been used as a measure of forward propu lsion (area under the positive curve) and braking (area under the negative curve) in people with hemiparesis. A recent study by Bowden used propulsive AP GRF as a performance measure to quantify the mechanical contribution of the paretic leg to forward p rogression in hemiparetic walking. 46 The percentage of propulsion generated by the paretic leg was found to be 16%, 36% and 49% for those with severe, moderate and mild hemiparesis as assessed by the Brunnstrom stages 47 respectively as
24 compared to the ex pected figure of close to 50% in normal walking. 46 On the other hand, previous estimates based on mechanical work calculations had suggested that the paretic l eg does 30 40% of the total mechanical work over the gait cycle regardless of hemiparetic severity. 16 Hemiparetic walking is characterized by joint moments and powers that are g reatly reduced as compared to controls walking at their self selected speed. However, when compared to individuals walking at matched speeds the differences are fewer. 48 At matched speeds paretic leg joint moments and power profiles are similar in pattern, but reduced in amplitudes, as compared to non paretic legs. Th us, the main power generation bursts in hemiparetic walking are the same as in normal walking 16 The following power bursts are among the ones affected after stroke: power gener ation burst associated with ipsilateral ankle plantar flexion moment in pre swing (A2), contralateral hip extension moment during initial double support (H1), ipsilateral hip flexion moment during pre swing (H3) Olney et al. showed that ankle joint plantar flexor power (A2) was barely evident in the paretic leg. 16 The A2 burst is greatly reduced on the paretic side and is shown to be compensated by H3 hip flexor moment. 49 In contrast to the paretic leg, the non paretic A2 burst (plantar flexor power generation) was found to be equal or great er than in speed matched controls. 50 Nadeau et al reported that fast walking hemiparetic individuals compensated for plantarflexor weakness by increased pre swin g hip flexor moments and powers. 51 Hip flexor moments and powers seem to be reduced for slow wal kers and increased for fast walkers as compared to normal controls. 8 16
25 The other potential mechanism for increased positive power generation during fast walking is the hip extensor burst in initial double support (H1). Although H1 increases with increasing speed across subjects 16 and after rehabilitation 50 overall it contributes less than the other two bursts. Interestingly, non paretic H1 increases to compensate in hemiparetics with slow walking speed. 16 The next section will delineate the underlying neuro musculo skeletal impairment s that lead to the above mentioned walking impairments in individuals with stroke. 1.4. Underlying Neuro musculo skeletal Impairments 1.4.1 Weakness Almost 80 90% of all individuals with stroke experience paresis or weakness 52 Weakness makes it difficult to generate tension or forces necessary for initiating and controlling movement and maintaining stability. The degree of weakness may vary from a complete inability to achieve any visible contracti on to measureable impairments in force production. Distal muscles such as ankle plantarflexors are more affected than the proxi mal muscles such as hip flexors 53 Weakness post stroke is referred to a s hemiparesis or hemiplegia on the contralesional side of the body. However, emerging unaffected ipsilesional side. 54 Paretic muscles are known to fatigue easily as well, hence decreasing the endurance for walking or performing other tasks. Although, weakness has mostly been studied in the context of muscle atrophy and a reduction in the cross sectional area of the muscle, force produci ng capacity is a neurological phenomenon and also depends on the capacity of the nervous system to recruit and modulate motor unit activity. 55 Hence weakness is now understood to occur
26 as a result of specific changes occurring both in the muscle and the descending central motor drive that activates muscle. However, little information is available regarding muscle structure and quality in person post stroke hemiplegia. Hence, muscle atrophy or reduction in the cross sectional area in muscles as a cause of weakness after stroke is not yet well established. Therefore, the significance of muscle structural changes to weakness post stroke has to be evaluated using more sensitive and reliable measures. On the other hand it has been shown that muscular weakness in stroke results from failure to adequately activate motor units supplying that muscle. 56 Reduced neural drive activate the muscle and ca n be attributed to damaged descending motor tracts following stroke. 57 58 It has been shown that muscle activated directly through electrical stimulation results in forces comparable to healthy controls 59 strengthening the argument that hemiparetic weakness results from impaired neural activation. 1.4.2. Abnormal Muscle Synergies/ Abnormal Muscle Activation Pattern multiple joints and body segments resulting in stereotyped and relatively fixed patterns 60 Individuals who have impaired selective movement control can utilize mass extension and flexion patterns of the lower extremity for stance and limb advancement during walking. Individuals who are more impaired will depend more on abnormal muscle synergies The mass extension pattern does not have the normal graduated increases in muscle activation necessary for controlled knee flexion in initial double limb support or ankle dorsiflexion in single limb stance. On the other hand, the flexion pattern can limit stride length when knee extension in terminal swing is restricted while the hip and knee continue to flex. 48
27 Walking after stroke is associated with abnormal muscle activation pa tterns. These abnormal muscle activation pattern reflect paresis, spasticity, and as historically reported, excessive muscle co activation. 15 61 Following stroke, the tempo ral ordering of muscle activity during walking can be disrupted, however, it has been shown that there is considerable intersubject variability and the hemiparetic population does not have one characteristic abnormal muscle activation pattern. Although som e of these abnormalities may be related to primary impairments in the temporal control of muscle activity, others are likely to reflect compensatory activity to optimize the gait pattern in the presence of muscular weakness and reduced coordinative control (for e.g., increased duration of biceps femoris rectus femoris coactivity during the single support phase). 62 1.4. 3 Proprioception The control of gait is based on the integration of both the peripheral sensory inputs and the descending supraspinal inputs. Sensory inputs play several important roles in the control of locomotion. Sensory inputs such as the hip angle an d load on the extensor muscles of the lower extremity triggers the stance to swing initiation 63 Thus loss of proprioceptive cues that normally signal hyperextension in the hip and the termination of stance can result in the delayed initiation of swing phase 63 In addition sensory inputs are necessary for adapting locomotor patterns to changes in environmental demands. Moreover, proprioceptively mediated stretch reflexes are modulated throughout the gait cycle. Proprioceptive loss in the lower extremity tends t o be more severe distally. 64
28 1.4.4 Disturbance s in Postural Control and Balance Locomotion is characterized by three essential requirements: progression, stability and adaptation. Stability is required to establish and maintain an appropriate posture for locomotion and the demand for dynamic stability of the moving body. Dynamic stability entails counteracting not only the force of gravity but other expected and unexpected forces as well. 65 Hence, balance or stability is essential for the task of walking. Balance is frequently disturbed following stroke wi th impairments in steadiness, symmetry, and dynamic stability common. Problems may exist when reacting to a destabilizing external force (reactive postural control) or during self initiated movements (anticipatory postural control). For example single limb stance phase is decreased on the paretic side as a result of inability of the paretic limb to maintain balance during mid stance and also to maintain balance when perturbation is caused by push off on the opposite side. Thus the patient may be unable to m aintain balance in standing or to move in a weight bearing posture without loss of balance. Disruptions of central sensorimotor processing may lead to an inability to adapt postural movements to changing task and environmental demands and impair motor lear ning. Delays in the onset of motor activity, abnormal timing and sequencing of muscle activity and abnormal co contraction and weakness all contribute to the balance problem. For example, proximal muscles may be activated in advance of distal muscles or in some patients, very late. Compensatory responses typically include excessive knee and hip movements. Corrective responses to perturbations and destabilizing forces are frequently inadequate and may result in loss of balance resulting in falls in individua ls with stroke. 64
29 Over time various therapeutic approaches targeting these underlying musculo skeletal impairments have been used to treat individuals with stroke. The next section will discuss some of the most recent therapeutic approaches used in the rehabilitation of gait post stroke. 1.5 Current Therapeutic A pproaches Behavioral manifestations of walking dysfunction post stroke emerge as a result of the biomechanical constraints of the musculoskeletal system and disturbances in the neural control of walking. Individual Impairments such as weaknes s, spasticity, abnormal muscle activation contribute to the aberrant locomotor patterns associated with post stroke hemiparesis. Recently, gait rehabilitation has steered towards therapeutic approaches derived from understanding the biomechanical and neuro logic mechanisms that result in walking impairment after stroke. 4 8 Prominent rehabilitation techniques being studied currently include resisted lower extremity strengthening and task specific training approaches. 66 68 Some o f these rehabilitation techniques are also used in combination to further optimize the effects of training. The effectiveness of some of these rehabilitation techniques for improving gait function post stroke are further discussed in detail. 1.5.1 Strengt h T raining Weakness is one of the significant impairments that are responsible for locomotor disability after stroke. 39 49 69 Although weakness, or paresis, of the contralesional side has been the focus of research for a long time, reduction in the force production and power generation of lower extremity muscles on the ipsilateral or the less affected side are also reported. 70 Moreover, weakness of the lower limb muscles and inability to generate power have been shown to correlate with locomotor performance such as
30 walking speed, stair climbing. 39 49 However, strength training for lower limb muscles after stroke has been questioned in the past by therapists because of the concern that resistance training may exacerbate spasticity a nd reinforce abnormal movement patterns. There is evidence that refutes this notion by showing that strength training leads to improvements in both lower limb muscle strength and gait performance without increasing spasticity. 71 72 This literature review for efficacy of strength training is based on studies from 1996 present, in stroke subjects at all stages of recovery and where strength training was not provided as an adjunct therapy. Thirteen studies were included. 73 85 Efficacy of strength training has been shown to be related to various factors: (1) whether the strength training program is directed at single muscle or groups of muscles that ar e typically activated during the stance or the swing phase of gait. For example, strength training targeting a single muscle group may result in strength gain without getting any improvement in the walking speed or endurance 73 on the other hand studies targeting functional strength training for the a ffected sideshows strength gains as well as increase in walking speed. 82 85 Another study by Patten et al. with dynamic resistance training done eccentrically using isokinetic exercises followed by clinic based gait training resulted in improvement in both the LE force production and walking speed. 86 (2) I ntensity of the resistance training for example, a study by Kim et al. compared isokinetic strengthening of the hip knee and ankle to passive range of motion of the hip knee and ankle using the same equipment. While lower extremity strength gains were seen in the experimental group, increased walking speed was observed in both the experimental and control groups. They suggested that participation in the exercise
31 resulted in as much benefit on walking function as resistance training. However, this could be a s a result of limitation in their strengthening device (Kin Com) as it requires a threshold torque to be achieved throughout the range of motion for completing the exercise. This could be a problem as stroke subjects are weak and may not be able to achieve this set threshold. A review of 8 studies (some of which were older than our search criteria) where strength training is done in isolation showed that strength training was effective in reducing the musculoskeletal impairments after stroke, though the res ults were inconclusive regarding its effect on performance of functional activities or participation in societal role. 87 Furthermore, conflicting results have been shown regarding the effectiveness of strength training with some studies showing bilateral improvements in strength 80 82 84 85 while others do not. 73 76 Similarly equivocal results are seen for gait function with some studies showing improvements in gait performance as measured by walking speed, six minute walk test, Timed Up and Go and spatiotemporal measures such as cadence and stride length 81 82 84 85 while other f ailed to show such improvements in walking function. 79 80 83 1.5.2 Locomotor T raining Recently efforts have also been focused on training paradigm that uses the concept of motor learning. The physiological basis of such training is derived largely from research on reduced animal preparations (e.g., spinalized cats) that were shown to generate a coordinated stepping pattern based on peripheral input while partially suspended with trunk support. They were also shown t o specifically respond in tasks
32 similar to ones they were trained with. Given these findings, interventions that are based on most of these criteria are used to train individuals post stroke and spinal cord injury to achieve a more normal walking pattern. Hence locomotor training is targeted towards: maximizing recovery by using normal movement patterns, minimizing the use of compensatory movement strategies, providing appropriate sensory input during walking (load on legs, normal arm, legs, pelvis and trun k kinematics coordinated stepping), training at speeds approximating normal walking speeds, promoting postural control while stepping and minimizing weight bearing through arms. This literature review for efficacy of locomotor training covered all the diff erent therapeutic approaches that follow the aforementioned criteria. These therapeutic techniques included treadmill training with or without body weight support, electromechanical gait trainer or other devices that facilitated this training. To understan d if these therapeutic approaches were superior to the conventional physical therapy provided in the clinics, we included only those studies that compared locomotor training to conventional physical therapy training of some kind. From year 2000 2012 we cam e up with 19 studies that fit our criteria. 22 89 105 A recently completed largest clinical trial (Locomotor Exp erience Applied Post stroke LEAPS) compared the effects of locomotor training and intense home based exercise training on walking recovery in sub acute stroke. No significant differences for the improvements were observed between the groups. Importantly, h owever the LEAPS trial did not use outcome measures which examine biomechanical or neuro physiological variables for understanding the mechanism of response to therapeutic intervention. Hence, in depth analysis cannot be made preventing the ability to unde rstand the mechanism of
33 response (or non response) 22 106 Moreover, conflicting results wer e seen with most of the studies showing an improvement in the gait function that was not different from the improvement gained by the conventional therapy group. 22 92 94 99 102 103 Walking spe ed 90 96 100 102 104 improved in many studies with improvements also in spatiotemporal factors 96 102 and symmetry. 95 Only two studies showed bilateral changes in the spatiotemporal factors and improved symmetry of walking. 95 102 The variations among the locomotor interventions studied and the outcomes measures selected to quantify improvements for these studies f urther makes it difficult to compare the results across studies. Therefore, the evidence for locomotor training efficacy is inconclusive and a unanimous decision cannot be made. 1.5.3 Speed T raining Repetitive task specific trainings such as treadmill tr aining with or without body weight support, locomotor training have been investigated and found to be an effective training tool, however, their superiority over other gait therapies is still disputed. Recently, since early 2000, studies have started inves tigating the effect of different parameters (e.g., amount and time of BWS, speed and acceleration of the treadmill belt) to optimize the effectiveness of the treadmill training. A few studies found that training at fast speeds could be an important factor to achieve this optimization. These studies base their theories on the principles of exercise physiology that emphasize that only sprint training at maximum speed provide adequate stimulus and challenge to the patient to produce meaningful adaptation and t o achieve optimum gait speed improvement. 107 There is also evidence to show that elec tromyographic activity, joint excursion angles and spatio temporal parameters vary considerably as a function of walking speed in healthy subjects 108 109 and similar variations a re also evident in
34 individuals with stroke. Olney et al showed a similar dependence on gait speed for the knee excursion with the maximum knee flexion during swing ranging from 38 degrees in slow walkers (average walking speed 0.25m/s) to 48 degrees in fas t walkers (average walking speed 0.25m/s) on the affected side. Likewise, a similar dependence on walking speed was seen for the knee flexion pattern in stance for fast walkers gradually advancing from 10 degree knee flexion at initial contact approaching extension in late stance as compared to slow walkers who started with 15 degrees of knee flexion at initial contact and were not able to modulate it even during late stance. 8 Hence it appears that even training at these speeds will be conducive to achieving these a daptations in their walking pattern. A search for training based on alteration or adjustment of speed included 6 studies (from 2001 2012) looking at the effect of treadmill training at speeds comparable to healthy controls and how it affects the gait patt ern. 110 114 In a study by Pohl et al. structured speed dependent treadmill training (STT) was compared to: a) limited progressive treadmill training (LTT) where t he speed was improved by 5% every week during the 4 weeks of training and b) conventional gait training based on the principles of proprioceptive neuromuscular facilitation and Bobath. 111 In STT the individuals were trained with an interval program where the treadmill speed was increased in increments of 10% if tolerated by the patient. The speed was increased at least by a factor of 3 and at most by a factor of 5 during a t raining session. Individuals who trained with the STT improved the most with an increase in the fastest comfortable walking speed from 0.61 m/sec to 1.63 m/sec, in cadence from 81.6 to 128.8 steps/min, in stride length from 0.42 to 0.72 m and in the
35 Functi onal Ambulation Category score from 3.7 to 5. 111 Another study by Sullivan et al. also investigated the effect of training speed on self selected overground walking speed. They compared a group that trained at fast speed (0.9m/s) to groups trained at slow (0.2m/s) or variable speeds (0.2, 0.45, 0.7 and 0.9m/s). Although a statistically significant difference was not revealed, the fast trained group did reveal a trend with a n improvement of 0.15m/s as compared to 0.06m/s for the slow and 0.07m/sec for the variable group (cite). This study also showed retention of the improvements even 3 months post training. 113 Improvements in gait speed, spatiotemporal symmetry, joint excursion angles (knee flexion during swing and hip extension at late stance) and muscle activation for both the paretic and the non paretic side were seen with fast walking with or without BWS. 112 Overall, it has been seen that trainin g with fast speed on treadmill can induce improvements in walking ability such as the self selected and fast walking speed and walking pattern i.e. quality such as spatiotemporal symmetry, joint excursion angles and muscle activation, bilaterally. Two stud ies also found bilateral improvements with improvements in spatiotemporal measures 114 symmetry in spatiotemporal measures 112 114 bilateral improvement in joint excursion and muscle activation 112 with training with fast speed, while other studies did not use side specific measures or reported only unilateral effects 1.6 Recovery of Walking Function in Stroke H emiparesis Various therapeutic approaches have shown efficacy for improving walking function at the level of impairments as seen by improvements in: strength, balance, spatiotemporal symmetry, improved joint excursion, improved muscle activity and clinical measures including the Rivermead Mobility Index (RMI), the Funct ional
36 Independence Measure. Other improvements were seen at the level of walking ability as seen by improvement in the self selected gait speed, maximal gait speed, six minute walk test, timed Up and Go, step test, Functional Ambulation Categories (FAC). V arious studies also show decreased energy cost and improved walking distance and endurance. Improvements were also seen at the level of participation as seen by improvement in the functional outcome scores such as Stroke Impact Scale (SIS). Most of the stu dies did not show any worsening of spasticity as seen with the Modified Ashworth Scale. Hence, there is sufficient evidence to suggest that there is potential of achieving improved walking function post stroke. However, even though improvements were seen i n most of the components of walking as defined by the International Classification of Functioning, Disability and Health (ICF), no one specific therapeutic approach investigated to date seemed to achieve all the improvements. Hence there is a need to under stand the various factors which may be responsible for the capacity to recover movement control post stroke as indicated by changes in force production, improved movement selectivity and appropriate neural activation as reflected by the equivocal results s een with different therapeutic approaches. These factors may include the intensity or dose of the treatment, the assumptions underlying the treatment itself or it may be the heterogeneity among the stroke population resulting in individuals who respond to Critical evaluation of any therapeutic approach may involve an analysis to get to the heart of the assumptions that guide the approach. Assumptions underlying therapeutic approaches in neurorehabilitation have usually b een implicit and have developed in parallel with the developing theories in neurophysiology. 115
37 Neurorehabilitation approaches have gradually moved from just focusing on muscle re educatio n techniques to sensorimotor treatment approaches such as Rood Proprioceptive Neuromuscular Facilitation (PNF) and Neurodevelopmental Treatment (NDT to the approaches used more currently based on the current theories of motor learning and neuroplasticity such as task specific gait training, speed training. There is no single ingredient that goes into the recipe of a successful factors and theories may guide the deve lopment of a successful therapeutic approach. changing speed and load during walking, forcing normal gait pattern during training, b.) Motor learning refers to the acquisition or modification of movement in normal individuals. In populations i results from pra ctice or experience, cannot be measured directly; instead it is inferred from behavior and finally should produce relatively permanent changes in behavior; thus short term alterations are not thought of as learning 60 permanent change in behavior and not just facilitated temporary changes in motor behavior as seen during a single training session.
38 Neural plasticity. Neural plasticity is the ability of the nervous system to show modification in its structure and function. These changes occur at different sites in the nervous system (i.e., in the brain, spinal cord, motor neuron e tc), at different stages of the lifespan (i.e., infancy, adulthood, after injury to the nervous system, etc.), on persistent. Motor learning Motor learning can be seen as a continuum of short term to long term changes in the ability to produce skilled actions. The gradual shift from short to long term learning reflects a move along the continuum of neural modifiability, as increased synaptic efficiency gives way to structura l changes, which are the underpinning of long term modification of behavior. 60 This is the process of neuroplasticity underlying learning a skill, be i t in a healthy nervous system or after neurological insult. Factors such as the onset, intensity and type of training, training at speeds comparable to speed in normal healthy controls, by forcing the normal gait pattern and providing sensory, visual and a uditory cues all affect the process of neuroplasticity. A once tenuous notion that functions of the cerebral cortex are alterable in adult mammals has developed into a neuroscientific tenet. The phenomenon of neural plasticity and the study of its unde rlying mechanisms have rapidly migrated from the laboratory to the clinic, as new interventional strategies are now conceptualized in relation to their ability to encourage adaptive plasticity. Given that we no longer consider the adult brain to be hard w ired and it is currently believed that the human CNS can repair itself, it seems possible to recover
39 and restore normal walking function in individuals with neurological damage such as a stroke. Moreover, even though it has been shown that current therapeu tic approaches, which are based in part on these now accepted neuroscientific tenets do in fact have the potential to achieve recovery of function, the results have been inconsistent. A recent clinical trial has reported that after 1 year post stroke, i mprovement was seen for only 52% of the individuals who were treated in their walking function 22 Hence and out ne xt step may be to understand and differentiate the characteristics of r esponders vs. n on responders. 1.7. Responders vs. Non responders It is well known that physical manifestations of stroke are heterogeneous making it difficult to understand the effects of treatment for each individual and unreasonabl e to expect the results of same magnitude in individuals treated with a particular therapy 116 117 Different factors including: chronicity of injury, the severity of motor impairments, specific characteristics of gait dysfunction and the intensity and the duration of the treatment provided are related to the variability of gains in walking ability observed in many intervention studies 118 We believe that another important factor contributing to this heterogenei ty stems from a combination of r esponders (RES) vs. Non responders (NRES) to therapy. Ernst in his review on stroke rehabilitation in 1990 expressed a urgent need to design well planned clinical trials aimed at find ing the best approach and discriminating potential responders 119 Although, various studies have so far been conducted to study the effectiveness of various treatment approaches to find the best approach, until recently studies have not focused on identifying responders. Mulroy et al., 2010
40 attempted to ident ify gait parameters associated with improved walking speed after body weight supported treadmill training (BWSTT). Individuals who increased their self selected walking speed by more than 0.08m/s were identified as a high response group and displayed great er increases hip extension angle and hip flexion power in terminal stance as well as higher intensity of soleus muscle EMG activity during walking 120 Another study by Bowden et al., 2012 attempted to identify the clinical measure s associated with individuals who respond with clinically meaningful changes in walking velocity after locomotor training 1 21 Individuals who improved their walking speed by more than 0.16m/s were identified as responders and showed significant gains in variables evaluating motor control, balance, functional walking ability and endurance. 1.7 Objective of this D issertation The overall objective of this dissertation to understand this variability among individuals post stroke by studying the characteristics of therapeutic responders and non responders, identified based on clinically important differences in their walking spe ed following intervention. We also aim to understand the mechanism that underlies improvements seen for responders vs. non responders. This dissertation will attempt to answer the following specific questions: Clinical characteristics of r esponders Do clinical scores help predict Responders vs. Non responders? Are there any clinical characteristics which can predict responders vs. non responders at baseline ? Biomechanical profile of the r esponders Do the responders have a different walking pattern tha n the Non responders differentiating them at baseline or post intervention as seen by biomechanical characteristics of walking (i.e., kinematics and kinetics )
41 Me chanism of improvement for the r esponders Are there differences in the way neuro mechanical mechanism of recovery in responders and non responders following intervention? Predi cting the potential responders. What are the key gait parameters critical to walking recovery and predictive of potential responders at baseline ? Chapters 3, 4, 5 and 6 of this dissertation describe the individual studies done to answer the questions mentioned above.
42 CHAPTER 2 COMMON METHODS This dissertation will utilize clinical, biomechanical and statistical measures to: 1) differentiate individuals who do and do not re spond to therapeutic i ntervention post stroke (i.e., responders and n on responders), 2) unde rstand the characteristics of responders and n on responders, and 3) to id entify parameters that predict r esponders at baseline. All the methodological details will b e provided in this chapter. In E xperiment 1 we studied the differential effects of power versus gait training and the differential effects of concentric versus eccentric mode of powe r training. We also identified responder and n on responders based on imp rovements in walki ng speed post intervention. In E xperiment 2 we will look at biomechanical measures such as joint angles, moments and power to und erstand the characteristics of responders and n on responders followed by E xperiment 3 where we study the diff erential responses in ground reaction force measures such as impulses and paretic propulsion, EMG during walking and the isokinetic muscle strength post intervention for responders and n on responders. Experiment 4 utilized a multivariate analysis to identi fy key gait parameters which are critical to walking function and will help us identify potential r esponders and non responders at baseline. 2.1 Subjects 2.1.1. Participants Thirty five individuals with hemiparesis resulting from a single cortical or subco rtical stroke (confirmed by CT or MRI), between 6 18 months prior to the study, who were categorized as at least unlimited household ambulators (e.g. > 0.3 m/s) 122 and were able to walk at least 10 m independently with or without an assistive device
43 participated. Exclusion criteria included: 1) unstable cardiovascular, orthopedic, or neurologic conditions, 2) uncontrolled diabetes that would preclude exercise of moderate intensity, or 3) significant impairment affecting the ability to follow directions. Participants were recruited from local hospitals, rehabilitation centers, and stroke associations. All procedures were approved by the Stanford University panels on human subjects research and all participants provided written, informed consent prior to study involvement. Hemiparetic participant demographics and clinical characteristics are presented in Table 2 1. For comparison, no rmative data were collected for 10 Healthy volunteers with average age of 42.7 11.03 year, 4 female, having no history of neurologic or orthopedic problems that could impair walking function. 2.1.2. Experimental Design Participants post stroke underwent a staged intervention involving 5 weeks (15 sessions) of unilateral paretic limb power training followed by 3 weeks (9 sessions) of clinic based gait training. During the power training stage, participants were randomized to either concentric or eccentric power training. Figure 2 1 illustrates the flow of participants through all stages of the study. 2.1.3. Randomization and Blinding To assure baseline equivalence between study groups, participants were stratified using the synergy sub score (22 points) 71 123 124 of the lower extremity Fugl Meyer Motor Assess ment 125 Participants scoring <18 were classified as lower functioning while those scoring 1 8 were classified as higher functioning. Separate random orders were prepared for higher and lower functioning participants and allocated to sealed envelopes that were kept in a locked drawer. Following baseline
44 clinical assessment, including determination of hemiparetic severity, the blinded evaluator drew a sequentially numbered sealed envelope from the appropriate group (i.e., higher vs. lower). This envelope was given to the treating physical therapist who subsequently opened it to reveal the treatment group assignment (i.e., concentric vs. eccentric). Participants were informed that the study goal was to investigate the effects of dynamic resistance training (e.g., power training) on locomotor function and were actively counseled to not discuss the spec ific details of the therapeutic activities with study personnel other than the treatment physical therapist. 2.1.4. Identifying Responders vs. Non Responders Although walking speed could change significantly it is quite possible that the change although si gnificant statistically may have little clinical significance. Hence, over the period of time various measures have been developed to account for meaningful change in walking speed. Contemporarily, two broad categories exist to determine meaningful change in an outcome measure: the distribution based and the anchor based approaches 126 Minimal clinica lly important difference (MCID) and Minimal important difference (MID) are two prominent such meas ures reported in the literature although they are often used interchangeably. MCID is a anchor based measure and is defined as the minimal amount of change t hat is important to the patient 127 The advantage of this anchor based approach is that the change in the outcome measure is linked to a meaningful external anchor representative of improvement perceived as beneficial by patients 128 MCID for the walking speed has been calculated by researches by using differe nt external anchors. For example, Tilson et al. determined MCID of 0.16m/s for self selected walking speed (SSWS) in individuals with subacute stroke in association with an improvement in the
45 modified Rankin Scale. However, various disadvantages in MCID ha ve also been documented including the variability among the MCID scores based on the method used to calculate it or external criteria selected or the effect of recall bias on long term responsiveness etc 129 130 Consequently, MCID scores are affected by subjective decisions taken by the patient or the clinician or researchers while calculating the MCID. MID on the other hand, is a distribution based measure which re lies on the statistical and the psychometric property of a measure in the population. MID is considered to be the minimal amount of change that is not likely to be due to random variation in measurement. It is sample specific and hence is not affected by t he demographics or the patho anatomic elements of the population sample. It has been shown that the minimal change calculated by the anchor based methods such as MCID are equivalent to half a standard deviation 131 which is how the MID is calculated in this study. Responders were identified as individuals who improved in their primary outcome measure of walking speed by more than 1 minimal i mportant difference (MID), after the complete 8 weeks o f staged intervention. Half of standard deviation for walking speed at baseline was used for calculating the MID Since walking speeds were available for both baseline and post gait intervention for 32 individuals we were able to identify them as either responders or non responders. Demographics and clinical characteristics for both the responders and non responders are presented in Table 2 1. 2.2. Measures This dissertation will utilize clinical, biome chanical and statistical measures to: 1) differentiate individuals who do and do not respond to therapeutic i ntervention post stroke (i.e., responders and n on responders), 2) understand the characteristics of
46 responders and n on responders, and 3) to id ent ify parameters that predict r esponders at baseline. 2.2.1. Clinical Assessments We performed a battery of clinical assessments representing the body structure/function and activity levels of the International Classification of Functioning, Disability and H ealth (ICF) 132 and included: the lower extremity portion of the Fug l Meyer motor assessment 125 the synergy sub score of the lower extremity Fugl Meyer motor ass essment 71 123 124 the European Stroke Scale 133 the Six Minute Walk Test (6MWT) 134 135 the Timed Up and Go (TUG) 136 137 the Berg Balance Scale 138 139 and the Functional Independence Measure (FIM) 140 Both validity and reliability has previously been established in individuals post stroke for all the clinical measures that were used in this dissertation. 126.96.36.199. Lower e xtremity Fugl Meyer m otor a ssessment The lower extremity Fugl Meyer Motor Assessment (FMA) was used to measure the lower extremity (LE) motor and sensory impairment The FMA is a stroke specific, performance based impairment index designed to assess 5 domains: motor function, sensory function, balance, joint range of motion (ROM) and joint pain in individuals post stroke. The motor domain includes items measuring mov ement, coordination, and reflex action about the hip, knee and ankle. 125 141 The lower extremity subscale of the FMA ranges from 0 (hemiplegia) to a maximum of 100 points (normal LE motor performance), divided into 34 points for motor function, 12 points for sensory function, 14 points for sitting and standing balanc e, 20 points for joint ROM and 20 points for joint pain.
47 The FMA is classified as a body structure measure in the ICF and is one of the most widely used quantitative measures of motor impairment. The psychometric properties of the FMA have been establishe d, shown to have high internal consistency, inter rater reliability, and test retest reliability 142 145 188.8.131.52. Lower e xtremity Fugl Meyer s ynergy s ub score B runnstrom has defined various stages of motor recovery and these stages have been used as a measure of hemiparetic severity. 47 The synergy sub score has been adopted from the Lower Extremity Fugl Meyer Assessment and is based on the same concept of progression from one level or stage of motor recovery to the next. 71 123 124 The synergy sub score is assessed by using the portion of the Fugl Meyer assessmen t that tests for movement within, combining and outside the synergy patterns. In this test participants are asked to perform movement within flexor and extensor synergy pattern, combining different synergy patterns and outside of synergy. The synergy sub s core ranges from 0 to 22. Various studies have used this sub score to categorize individuals into mild, moderate and severe hemiparesis categories. 71 123 184.108.40.206. European stroke s cale We used European stroke scale (ESS) as a measure of level of impairment of individuals with stroke. It consists of 14 items selected on the basis of their specificity and their prognostic value. The 14 items are: level of consciousness, comprehension, speech, visual field, gaze, facial movement, maintenance of arm position, arm raising, wrist extension, finger strength, and maintenance of leg position, leg flexing, foot dorsiflexion, and gait. 133
48 The clinometric properties of the ESS have been established, shown to have high interrater reliability (Kappa statistics range 0.62 to 0.85), intrarater reliability (Kappa statistics 133 220.127.116.11. Six minute walk test The six minute walk test (6MWT) was used as a straightforward measure of functional capacity, endurance for individuals with stroke. 146 147 In this test the distance that an individual can walk within six minutes is evaluated. The clinometric properties of the 6MWT are well established. It is shown to have high test retest reliability (Intra class correlation coefficient (ICC) =0.96 0.99) 148 149 and adequate inter and intra rater reliability (ICC = 0.74 and ICC =0.78 respectively) 150 18.104.22.168. Timed up and go The timed up and go (TUG) was used as a measure of general physical performance to assess mobility, balance and locomotor performance 137 151 152 The TUG tests the ability to perfor m sequential motor tasks relative to walking and turning. The participant is asked to stand up from a chair, walk a distance of 3 meters, turn around, walk back to the chair and sit down as fast and safely as they can. The TUG has been shown to have excel lent test retest reliability (ICC = 0.96) 148 excellent inter rater reliability (ICC = 0.98) 137 153 excellent intra rater reliability (ICC = 0.99) 137 22.214.171.124. Berg bala nce scale The Berg Balance Scale (BBS) was used to assess balance. The BBS has 14 items designed to assess static and dynamic balance objectively and measure fall risk in the adult population. As part of this test participants were asked to maintain a posi tion and complete movements of varying difficulty. Individual items are scored from 0 4 for
49 based on their ability to meet the demands of these various balance dimensions. The BBS takes 10 15 min and provides a global score calculated out of 56 points. Th e clinometric properties of the BBS have been established, shown to have excellent interrater reliability (ICC= 0.98), intrarater reliability (ICC = .97) and internal 138 It was also shown to have excellent test retest reliability (ICC =0.88) 154 126.96.36.199. Functional independence measure The Functional Indep endence Measure (FIM) was used to assess the ability of the participants to perform their activities of daily living 155 The FIM provides a uniform system of measurement for disability based on the International Classification of bility and indicates how much assistance is required for the individual to carry out activities of daily living (e.g., burden of care). The FIM involves 18 items assessing 6 areas of function and is composed of 13 motor and 5 cognitive tasks. Each item is scored from 0 7 and a final score is calculated ranging from 18 126 where 18 represents complete dependence and 126 represents complete independence. The psychometric properties of FIM are well established with excellent internal 156 excellent test retest reliability for Motor FIM (ICC=0.90) and Cognitive FIM (ICC=0.80) subscales 157 high intra rater reliabilities for total FIM, Motor FIM and Cognitive FIM (ICC = 0.98, 0.98 and 0.95, respectively) 158 and excellent inter rater reliability (ICC=0.96) 159
50 2.2.2. Three Dimensional Motion Analysis Three dimensional motion analysis is a highly sensitive assessment technique that allows us to study different facets of gait. Accurate description of the actions occurring at individual joints is necessary in order understand the impairments in a n individual joint actions and hence allows us to study complex motor behavior such as walking. Motion analysis allows us to distinguish between improvement in function due to recovery or compensation. Dynamic electromyography (EMG) performed concurrently provides an indirect indicator of muscle activation EMG can be recorded and analyzed to determine the timing and relative intensity of muscular effort. In addition force pl ate recordings quantify the functional demands being experienced during the weight bearing period. 188.8.131.52. Data collection Motion analysis was performed during walking using a seven camera Qualisys Motion Capture System 1 A modified Cleveland Clinic Mark er set including 38 marker placements was used to measure motion in six degrees of freedom (three rotations, three translations) for each segment. A minimum of three markers were placed on each segment to determine the position and orientation in a three d imensional space. 8 segments were defined: Trunk, Pelvis, Right thigh, Left Thigh, Right shank, Left shank, Right foot and Left foot. Twelve additional markers were placed during the static trial were used to determine the joint axis (flexion/extension) fo r a given joint and were consequently removed during dynamic walking trials to facilitate unencumbered motion 1 Copyright Qualisys Inc., East Wi ndsor, CT USA
51 of the subject during walking. Bilateral kinematics and kinetics were captured at 200Hz. Ground reaction forces were measured at 100 Hz using thre e synchronized force plates 2 3 positioned in the laboratory gait walkway. Surface electromyography (EMG) was recorded at 2000Hz for 8 muscles per leg using pre amplified electrodes 4 placed over the muscle bellies of: tibialis anterior, medial gastrocnemiu s, soleus, rectus femoris, vastus lateralis, biceps femoris, semitendinosus and gluteus medius. Data were collected as the participants with stroke walked at their self selected and fast speeds and the controls walked at their self selected and two or thre e slower speeds. selected speed. In addition, t he control subjects were asked to wa lk progressively slower than their self selected walking speed. Five or more trials of each speed condition (i.e., self selected and slow speeds) were collected in order to obtain a minimum of three isolated force plate strikes for each foot Subjects wore their usual footwear. Participants with stroke were asked to walk without their assistive devices and/or AFO if it was safe to do so. 184.108.40.206. Data reduction Marker data were labeled using the Qualysis Track Manager 5 and modeled in Visual3D 6 Kinematic a nd kinetic data were processed in the Visual3D to calculate joint 2 Copyright Bertec Corporation, Columbus, OH, USA, Model no. k81101/Type 4060 10 3 Copyright Advanced Mechanical Technology, Inc., Watertown, MA, USA, Model no. OR6 6 1000 4 Copyright Motion Lab Systems, Inc, Baton Rouge, LA, USA 5 Copyright 2011 Qualysis, Gothenburg Sweden 6 Copyright 2010 C Motion, Version 4.00.19, Inc C Motion, Germantown, Maryland
52 moment, angles and powers. An eight segment inertial model of each subject was used based on the data collected by Dempster (1955) 160 It consists of an upper trunk (including the mass of the head and arms), pelvis, two thighs, two shanks and t wo feet (incl uding the mass of the shoes). The gait events of heel strike and toe off for each foot were determined using a threshold on the vertical ground reaction force (F>20N) and target pattern recognition 161 All the events were visually inspected for accuracy and were modified if needed. Marker data were gap filled using interpolation and were filtered using second order Butterworth l ow pass filter (f c = 6Hz) and the force analog signals were filtered using second order Butterworth low pass filter (f c = 10Hz). Kinematic, kinetic and force data were then exported to matfiles. Custom designed MATLAB 7 programs were used to further analyze and extract kinematic, kinetic, force plate and EMG data. The post processed kinematic and kinetic data were then filtered using a fourth order Butterworth low pass filter (f c =10Hz). EMG data for this study were collected using a separate hardware and so ftware package and were processed and time synced to the kinematic and kinetic data using custom designed MATLAB programs. The EMG data were filtered using a fourth order Butterworth low pass filter (f c =10Hz). All the data were visually inspected in a cu stom designed MATLAB program to check for quality before they were extracted for further analysis. Kinematic, kinetic, force and EMG data were used to obtain the following parameters indicative of walking performance and pattern. Walking speed. Self selec ted walking speed overground was calculated using the kinematic trajectories of the foot marker. Self selected walking speed is an important 7 MathWorks Inc, Massachusetts, USA
53 measure of stroke recovery as it is easy to measure, reflects both physiological and functional changes 122 162 Spatiotemporal measures. To analyze if there were changes in the locomotor pattern of walking in individuals with stroke post intervention we measured var ious kinematic gait varia bles. Cadence and stride length were measured as walking speed is a product of cadence and stride length and any improvement in walking speed is accomplished through an improvement in these measures. Paretic single limb support (SLS), a meaningful and sens itive indicator of lower extremity function during gait reflecting the capacity to: support and transfer body weight between limbs while enabling forward progression was also recorded. We also recorded double limb support (DLS) phase I and phase II for th e paretic leg and Non paretic step length Further details about the varia bles used are given in Appendix A Joint angles, moments and power. Further analysis looked into even more details at the angle, moments and power to understand the characteristics of Responders and Non responders. The specific variables used are m entioned in detail in Appendix A Ground reaction forces. Variables were defined from the anterior posterior ground reaction forces (A P GRF) and were defined as follows: 1) propulsive im pulse is the time integral of the positive A P GRF, 2) braking impulse is the time integral of the negative A P GRF. Propulsive and braking impulses were calculated within each bin of the stance phase. The percentage of total propulsion generated by the pa retic leg was calculated by dividing the propulsive impulse of the paretic leg by the sum of the paretic and non paretic propulsive impulses and was referred to as Paretic propulsion (Pp). Pp
54 is a quantitative measure of the contribution of the paretic leg in propelling the center of mass forward during walking 46 Electromyography. Percentage integrated EMG was calculated for each bin for each of the eight muscl es. It is calculated as the area of EMG for each gait cycle bin normalized to the area of the EMG for total gait cycle. Bin analysis. The gait cycle was separated into six bins in order to analyze muscle activity or impulse generation or power produced at various time points in the gait cycle: 1) double limb support after (paretic/non paretic) foot strike, 2) the first 50% (of paretic/non paretic) single limb stance, 3) the second 50% of (paretic/non paretic) single limb stance, 4) double limb support prio r to (paretic/non paretic) swing, 5) the first 50% of (paretic/non paretic) swing, and 6) the second 50% of (paretic/non paretic) swing. 2.2.3. Strength 220.127.116.11. Data collection Lower Extremity Strength. Maximum voluntary isometric torques was obtained f or hip flexion, hip abduction, knee flexion, knee extension, Ankle plantarflexion and dorsiflexion for the paretic leg. For the non paretic leg maximum voluntary isometric torques were obtained for knee extension and flexion movement. Strength was measured using a Biodex System 3 Pro dynamometer 8 Subjects were seated with the back of the Biodex chair angled at 85 o and were positioned according to the operational manual for Biodex System 3 Pro dynamometer for hip flexion, knee extension, knee flexion and a nkle plantarflexion and dorsiflexion 163 For knee extension the test limb was 8 Copyright Biodex Medical Systems Inc., Shirley, NY, USA
55 secur ed to the dynamometer lever arm by a padded attachment. Custom attachments were fabricated to test hip abduction as represented in Figure 2 2 Subjects were instructed to keep their arms folded across their chest while performing the test and were strapped firmly to the Biodex to avoid extraneous movements. Passive torques. Passive torques was measured with the dynamometer by moving the limb in the passive mode at 10 deg/s. This measurement was used to account for limb weight and passive resistance to movem ent. Subjects were instructed to relax while the dynamometer moved the limb through the entire range of motion (ROM). At least 2 passive trials were collected for each muscle action. EMG was monitored to assure these measurements were obtained under fully passive conditions. Maximum voluntary isometric torque. Isometric strength was measured for ankle dorsiflexion and plantarflexion with the ankle in neutral (e.g., 90 o ), knee flexion and extension were tested with knee in 70 of flexion. Hip flexion was tested with the subject reclined (20 o ) and the hip positioned in 70 o of flexion. Hip abduction was tested with the subject reclined 45 o the hip positioned in 55 o of flexion, the knee full extended and supported against gravit y. Two trials, each lasting 5 sec, were collected for each joint action. A 1 min rest period was provided after each trial to minimize the effects of fatigue 164 A trial was repeated if there was more than 10% difference between 2 trials. 18.104.22.168. Data reduction The analog torque, position, and velocity signals were sampled concurrently from the dynamometer and lowpass filtered at 100 Hz using an analog hardware filter.
56 All data were sampled at 1 kHz and acquired digitally using a Powerlab/16SP A/D system and Chart 5.0 software 9 and saved directly to disk for offline analysis. 2.3. Intervention Participants underwent a staged intervention involving 5 weeks (15 sessions) of paretic limb power training followed by 3 weeks (9 sessions) of clinic based gait training. During the power training stage, participants were randomized to either concentric or eccentric power training. 2.3.1. Power Training Fifteen sessions of lower extremity resistance training was performed three days per week lasting 5 weeks, using a Biodex System 3 Pro isokinetic dynamometer (Biodex Medical Systems Inc., Shirley NY) for the paretic leg. Following muscle groups were trained: ankle dorsifle xors and plantarflexors, knee extensors and flexors, hip abductors and a multi segmental task involving hip flexion/extension, knee extension/flexion and ankle plantar/dorsiflexion engaging all these muscle groups together as in walking. Three sets of 10 r epetitions involving maximal effort dynamic contraction were performed at 3 different criterion velocities each week for knee flexion, knee extension and the combined multi segmental hip knee ankle movement. For hip abduction, ankle dorsiflexion and ankle plantarflexion training was only done at the two lower speeds because of the limited range of motion affecting the ability to reach higher criterion speeds. The criterion velocities were gradually varied each week by first increasing for week 2 and 3 and t hen again decreasing to progressively increase the chal lenge of the training program. To account for the reduced period of active 9 Copyright ADInstruments, C olorado Springs, CO, USA
57 contraction at higher speeds the number of sets were incre as ed to 4 in week 4. Figure 2 3 shows the exercise prescription used for the dynamic lower extremity power training. Each session lasted 90 minutes. For hip abduction and the multi segmental movement custom designed attachments were used to enable optimal biomechanical alignment for performance in a semirecumbent position and to deliver the closed chain multi segmental movement same as in strength testing. The positioning for these 2 movements is shown in F ig ure 2 2 Verbal encouragement was provided throughout the training sessions to motivate participants to exert maxima l effort for each contraction. The non paretic leg was not trained. 2.3.2. Gait Training Nine sessions of clinic based gait training were performed three days a week for three weeks with a single session lasting 90 min. Each session involved: stretching (1 5 minutes), activities to target specific components of gait (30 minutes), balance and/or obstacle course (15 minutes) and treadmill walking (30 minutes). Participants usually performed muscle stretches on their own with therapist only assisting when requi red. Before working on the various components of gait participant usually did a warm up gait session where they walked back and forth in a hallway for about 5 min without any assistive devi ces or AFOs. Treatment goals for components of gait progressively a dvanced from weight acceptance (Week 1) to single limb support (Week 2) and limb advancement (Week 3) and were based on the principles of motor relearning 165 During each session participant performed 3 4 exercises focusing on the component of gait for that week and a note was made of the number of repetitions and sets of exercises performed by the participant. Each exercise was followed by walking to allow the participant to apply the concept they just practiced on to the task of walking. The
58 treadmill walking program involved interval training with short bouts (75 150 seconds) of ich was determined during the first session of each week program and was motivated by the approach of Pohl and co workers 111 Partial body weight support was r educed progre ssively from 30% (w eek 1) to 20 % (week 2) and 10 % (w eek 3). No therapist assistance was provided for either limb advancement or kinematics. 2.4 Statistical Analyses 2.4.1. Statisti cal analysis for C hapter s 3, 4 and 5 Statistical analyses for C hapter s 3. 4 and 5 were done using the PASW statistics in windows Significance levels less than 0.05 represented statistical significance. Statistical analysis was done as a whole group as well as for the RES and NRES group. Participants were stratified as Res or N RES on the basis of their response to the selected walking speed. For the primary outcome of gait speed changes across the different treatments were tested using repeated measure ANOVA on the raw scores (for Baseline, post POW and post GAIT ) for the overall cohort Pair wise comparisons revealed where the changes were. For all the other outcomes Mann Whitney U test was used compare the RES and the NRES at baseline and the WIlcoxon signed rank test was used to compare the p re training to post training scores. exact test was used to compare the RES and the NRES at baseline.
59 2.4.2. Statistical analysis for C hapter 6 MATLAB programs were created and exec uted to run the Sure Independent Screening (SIS) to reduce the dimension of the data to 8 degree of freedom followed by further reduction of the dimension to 3 degree of freedom by fitting the data by Envelope model. Estimates for the means of dependent va riable (Y) for the two groups (Responder and Non responder) and other constituent parameters were calculated by envelope model. These estimates were used in the Fischer Discriminant Analysis to find the discriminant equation to classify any new observation into one of the 2 groups.
60 Table 2 1. Participant demographics and clinical characteristics Characteristics Hemiparetic (n=35) Responders (n=15) Non responders (n=17) Mean age, yr ( SD) 61.7 ( 10.6) 55.3 ( 10.2) 67.05 ( 8.7) Gender Ma le 26 12 12 Female 9 3 5 Time since stroke onset, mo ( SD) 13.2 ( 4.7) 13.2 ( 5.9) 12.7 ( 3.7) Side affected Right 13 5 8 Left 22 10 9 Assistive device Yes 22 7 12 No 13 8 5 Berg Balance Scale (/56) Mean ( SD) 42.8 ( 6.3) 45.1 ( 4.9) 41.2( 7.1) Range 30 53 34 53 30 52 Total Fugl Meyer score (/100) Mean ( SD) 79.03 ( 8.5) 79.3 ( 8.3) 79.3 ( 8.9) Range 58 91 59 91 58 91 Fugl Meyer synergy score (/22) Mean ( SD) 15.3 ( 4.3) 15.5 ( 4.2) 15.2 ( 4.8) Range 3 21 3 21 3 21
61 Table 2 1. Continued. Characteristics Hemiparetic (n=35) Responders (n=15) Non responders (n=17) European stroke scale (/100) Mean ( SD) 7 1.4 ( 11.7) 70.8 ( 11.7) 72.2( 12.8) Range 46 93 46 93 50 93 Functional independence measure (/91) Mean ( SD) 81.7 ( 6.3) 82.36 ( 6.1) 81.9( 6.5) Range 68 91 72 91 68 91 Six minute walk test (m) Mean ( S D) 207.7 ( 117.8) 220.5 ( 108.3) 194.7( 134.02) Range 59 435.6 66.9 428.3 59 435.6 Timed up and go test (sec) Mean ( SD) 45.1 ( 4.9) 24.5( 12.6) 31.6( 16.07) Range 8.6 56 10.3 52 8.6 56 Self selected walking speed (m/s) Mean ( SD) 0.43 ( 0.25) 0.45 ( 0.24) 0.39 ( 0.23) Functional Classification 11 5 6 Low ( FM synergy score < 18) 24 10 11 Training classification Eccentric 18 8 9 Concentric 17 7 8
62 Figure 2 1. Consort diagram of participant progression through the trial.
63 Photo(s) courtesy of Shilpa Patil Sharma Figure 2 2.Shows the positioning and the custom attachments for p ower training and strength test ing for A) hip a bduction movement and B) a combined lower extremity movement involving hip flexion, knee f lexion and ankle dorsiflexion.
64 Figure 2 3 Exercise prescription showing the progression for the lower extremity power training.
65 CHAPTER 3 CLINICAL CHARACTERIST ICS: RESPONDERS VS. NON RESPONDERS 3.1. Background Stroke is the leading cause of physical disability in adults worldwide. 15 million people suffer from stroke annually, 60% of whom die or become permanently disabled even in countries with advanced technol ogies and facilities 166 In the United States o ver two thirds of individual s in the acute phase post stroke experience walking impairment but only one third of these individuals improve sufficiently to achieve independent walking 167 Because i mpaired walking contributes significantly to functional disability following stroke 19 it is not surprising that improved mobility and restoration of walking are among the most frequently articulated goals of stroke rehabilitation 6 20 21 Gait dysfunction following str oke is characterized by : slow walking speed, reduced cadence, stride length, longer stance phase on the less affected side and reduced joint excursions 8 10 ; asymmet ry in temporal, spatial, kinematic and kinetic gait variables 11 14 ; abnormal muscle activation patterns 15 16 and increased mechanical energetic and m etabolic costs 17 18 A combination of weakness of the affected side and compensation by the less affecte d side, contributes significantly to hemiparetic gait dysfunction. For example, plantarflexor weakness is an important factor that limits gait speed in individuals post stroke and is often compensated by hip flexors of that side 49 Impair ed hip and ankle power generation in the paretic limb limits the capacity to increase walking speed. 168 There is a clea r need to improve the biomechanical efficiency of individuals post stroke and reduce walking disability Consequently, there is a need to understand these gait impairments to better address their role in rehabilitation of walking.
66 Despite recognition of t he problem there is currently no consensus regarding the most effective approach to promote walking recovery 169 Some treatment approaches, such as task specific locomotor training using partial body weight support, have been considered to determine their efficacy as compared to traditional phy sical therapy approaches 22 94 105 An equally import ant factor pertains to the capacity for recovery of locomotor function following stroke. Notable in this regard are results of a recent multi site clinical trial demonstrating improved walking function in only 52% of individuals undergoing rehabilitation i n the sub acute period after stroke 22 H emiparetic weakness i.e., inability to generate normal levels of force in the limbs contralateral to the brain hemisphere affected by stroke is one of the most prominent manifestations post stroke 72 C orrelat ion between hemiparetic weakness, decreased mobility function and gait speed 170 172 suggests its role in limiting motor performance post stroke 172 173 Weakness can be remediated through systematic strengthening. Traditionally, h igh effort activities including strengthening were believed to exacerbate spasticity and reinforce aberrant spinal circuits thus were strictly proscribed in neurorehabilitation 174 Recently, however, the effects of strength ening have been investigated in persons post stroke with no evide nce of negative consequences, including increased spasticity 73 74 79 84 Moreover, this recent evidence suggests that strength training results in positive changes on various indices of functional mobility 72 74 Importantly none of these studies have evaluated the mechanism underlying improvements in strength and function following rehab ilitation for post stroke hemiplegia 72
67 S elf selected o verground walking speed (SSWS) has been found to predict community ambulation 122 and thus is the measure most typically used to evaluate outcome s of clinical studies for walking dysfunction 46 50 However, walking speed provides only a global indicator without information regarding the mechanisms that mediate change in walking function For example, c ompensatory action by the nonparetic leg can result in a relatively functional walking speed despite poor coordination of the paretic leg 46 49 168 Of note are recent studies that reveal improvements in walking speed and clinical assessment scales in the absence of improved coordination or muscle activation patterns 62 175 Although improvement in SSWS is generally considered a positive clinical outcome it fails to address whether intervention improv es or restores the fundamental walking pattern after stroke and thus whether intervention related changes reveal compensation or recovery. Here we investigated the therapeutic effects of a rehabilitation intervention for walking recovery in persons post s troke. Our primary aim was to differentiate effects of lower extremity power training and clinic based gait training Our secondary aim was to identify the presence of therapeutic responders and non responders to determine whether intrinsic, subject specif ic factors, specific characteristics of the therapeutic interventions or the combination of these effects mediate t reatment outcomes post stroke. 3.2. Methods 3.2.1. Participants Thirty five individuals with hemiparesis resulting from a single cortical or subcortical stroke (confirmed by CT or MRI), between 6 18 months prior to enrollment, able to walk at least 10 m independently, with or without an assistive device,
68 participated. Exclusion criteria for participation were: 1) unstable cardiovascular, orthopedic, or neurologic conditions, 2) uncontrolled diabetes, 3) conditions that would preclude exercise of moderate intensity, or 4) significant impairment affecting the ability to follow directions. All participants gave written informed consent prior to involvement in the study. Participant demographics and clinical characteristics are presented in Table 3 1. 3.2.2. Experimental Design To answer our prima ry question participants underwent a staged intervention involving 5 weeks (15 sessions) of paretic limb power training followed by 3 weeks (9 sessions) of clinic based gait training. Figure 3 1 illustrates the flow of participants through all stages of th e study. To assure baseline equivalence between groups, participants were classified as higher or lower functioning using the synergy subscore (22 points) 71 123 124 of the lower extremity Fugl Meyer motor assessment 125 (i.e., scor es <18 lower functioning 18 higher functioning ) Using separate random orders for higher and lower functioning, p articipants were randomized to either concentric or eccentri c power training. 3.2.3. Intervention 3.2.3 .1. Power training Dynamic resistance training was performed with the paretic (P) leg three days a week for 5 weeks (i.e., 15 sessions) using a Biodex System 3 Pro isokinetic dynamometer (Biodex Medical Systems I nc., Shirley NY). The f ollowing muscle groups were trained using maximal effort dynamic contraction s : ankle dorsiflexors and plantarflexors, knee extensors and flexors, hip abductors and a multi joint task involving hip flexion/extension, knee extension/fl exion and ankle plantar/dorsiflexion engaging all
69 joints in proportion s of motion similar to walking. F or knee flexion, knee extension and the combined multi joint hip knee ankle movement t hree sets of 10 repetitions were performed at 3 different criterion velocities each week. B ecause of the limited range of motion affecting the ability to reach higher criterion speeds training was performed at only two lower speeds f or hip abduction, ankle dorsiflexion and ankle plantarflexion. The criterion velocities w ere varied each week first increasing for weeks 2 and 3 and then decreasing for weeks 4 and 5 to progressively increase the chal lenge of the training program. To account for the reduced period of active contraction at higher speeds (i.e., work:rest ratio) and maintain comparable periods of active work across the program the number of sets was increased to 4 in week 3 Figure 3 2 illustrates the exercise prescription which was parameterized using power (i.e., j oint torque x angular velocity) 176 H ip abduction and the multi joint movement were performed using custom attachments designed to enable optimal biomechanical alignment f or performance (Figure 3 3 ) Each session lasted 90 minutes and was administered by a licensed physical therapist Verbal encouragement was provided throughout the training sessions to motivate participants to exert maximal effort for each contraction. The non paretic (NP) leg was not trained. 3.2.3 .2. Gait training C linic based gait training w as performed three days weekly for three weeks (i.e., 9 sessions). E ach session last ed 90 min and involved: stretching (15 minutes), activities to target specific com ponents of gait (30 minutes), balance and/or obstacle course (15 minutes), treadmill walking (30 minutes) and w as administered by a licensed physical therapist. At the beginning of each session, participants warmed up by walking overground for approximatel y 5 minutes without using any assistive devices or AFOs, if
70 possible. Treatment goals for components of gait progressively advanced from: weight acceptance (Week 1), to single limb support (Week 2), and limb advancement (Week 3) and treatment activities w ere based on the principles of motor relearning 165 Each session involved 3 4 exercises focusing on the component of gait prioritized f or the week T he number of repetitions and sets of exercises performed by the participant was noted Each exercise was followed by a short bout of overgound walking to allow the participant to apply the component just practiced to the whole task of walking The treadmill walking program, motivated by the approach of Pohl and co workers 111 involved interval training with short bouts (75 150 seconds) of walking and striding a t of each week. Partial body weight support, provided primarily for safety, was reduced progressively from 30% (Week 1) to 20% (Week 2) and 10% (Week 3). No physical assi stance was provided for either limb advancement or kinematics during treadmill walking, although verbal cues and coaching were provided by the therapist. 3.2.4 Measurements Participants were assessed at three time points: baseline (BAS), post power traini ng (POW) and post gait training (GAIT) Clinical Assessment. Because the focus of this investigation was demonstration of treatment efficacy 177 assessments representing the body structure/function and activity levels of the Inte rnational Classification of Functioning, Disability and Health 132 w ere included: the lower extremity portion of the Fugl Meyer motor assessment (FMA) 125 and the synergy subscore (FMA Synergy) 71 123 124 European Stro ke Scale (ESS) 133 Six Minute Walk Test (6MWT) 134 135 Timed Up and Go (TUG) 136 137 Berg Balance Scale (BBS) 13 8 139 and the Functional Independence Measure (FIM) 140
71 Instrumented Gait Analysis. Instrumented gait analysis was condu cted using a seven camera motion capture system (Qualysis, Inc., Goteborg, Sweden, 240 Hz) with three synchronized force plates (AMTI, Watertown, MA, USA and Bertec, Columbus, OH, USA, 100Hz) positioned in the laboratory walkway Data were collected using a modified Cleveland Clinic marker set (38 markers ) as participants walked at SSWS wearing their usual footwear and, if possible, no assistive device or AFO Five or more trials were collected to obtain a minimum of three isolated force plate strikes for e ach foot. Marker data were labeled using Qualysis Track Manager (Qualysis, Inc., Goteborg, Sweden Version 2.0 ); biomechanical modeling and identification of gait cycle events w as performed using Visual3D ( Version 4 .0 C motion, Rockville, MD). Gait param eters were extracted using custom written MATLAB (2007a, The MathWorks, Natick, MA, USA) scripts. 3.2.4 .1. Primary outcome measure. The primary outcome was overground SSWS To address our secondary aim, we identified responders and non responders as indiv iduals who achieved and retained a minimal important difference (MID) 178 in SSWS following both intervention stages. 3.2.4 .2. Secondary outcome measures The f ollowing secondary measures were studied t o determine if there were changes in the gait pattern post intervention Spatiotemporal Parameters. S patiotemporal parameters including: cadence, stride length P single limb support (PSLS), first and second P double limb support (PDLS1 PDLS2) and non paretic (NP) s tep length were calculated from marker data. Isometric Strength. Maximum voluntary isometric muscle torques was obtained for P leg hip flexion, hip abduction, knee flexion, knee extension, ankle plantarflexion
72 and dorsiflexion using a Biodex System 3 Pro d ynamometer 1 Standard positioning described in the Biodex manual was used for hip flexion, knee extension, knee flexion, ankle plantarflexion and dorsiflexion 163 H ip abduction was tested using a custom fabrica ted attachment (Figure 3 3 ). For each joint action, t wo trials, each lasting 5 sec, were collected with a 1 min rest period betwe en trial s to minimize effects of fatigue 164 A trial was repeated if the difference between 2 trials exceeded 10% 3.2.5 Data Analysis Statistical analyses were performed using SPSS (IBM SPSS Statistics 20.0, IBM Corporation, Armonk, NY, USA) with a priori significance established as p < 0.05. Due to the small sample siz e, all within and between group comparisons were performed using non parametric analyses withou t adjusting for multiple comparisons. P values are provided for all analyses. Primary Analysis. W e utilized repeated to test for changes across intervention phases ( BAS, POW, and GAIT ). Individual differences between BAS versus POW POW versus GAIT and BAS versus GAIT values for whole cohort were tested using Wilcoxon Signed Rank Test. We used the Wilcoxon Signed Rank test to test for effect s of the concentric versus eccentric mode of treatment following POW and GAIT The Mann Whit ney U test was used to compare concentric and eccentric group at BAS for continuous variables while the Fisher exact test was used for nominal variables. Secondary Analysis. For continuous variables the Mann Whitney U Test was used to compare responder s (RES) and non responder s (NRES) at BAS and the 1 Copyright Biodex Medical Systems Inc., Shirley, NY, USA
73 Wilcoxon Sign ed Rank Test was used to test for changes from BAS to GAIT for each group (i.e., RES, NRES) For comparing baseline equivalence between groups for nominal variables or when comparing the number o f individuals who improved within each group we utilized sided or 1 sided test Fisher exact test was based on the question to be answered. 3.3. Results 3.3.1. Differential Effects of Training and Mode of Strength Trai ning Our primary aims were to: 1) compare power training versus standard, clinic based gait training and 2) compare concentric versus eccentric mode s of power training on SSWS. At baseline no differences in: age, gender, time since stroke, severity, side affected, use of assistive device or clinical scores was revealed between the individuals trained concentrically or eccentrically. Demographics and clinical characteristics for concentric and eccentric trained groups are presented in Table 3 1. Significan t changes in SSWS were observed across both intervention phase s (p <.001) with significant increase s noted between BAS POW (0.08m/s, p <.001), POW GAIT (0.06 m/s, p=.001) and BAS GAIT (0.13m/s, p <.001) respectively. The magnitude of changes between the P OW and GAIT phases (i.e. BAS POW vs. POW GAIT) was not significantly different (p =0.654). More details can be found in Figure 3 2 and Table 3 2. N o significant differences were revealed between the concentric and the eccentric modes of training across the various intervention stage s indicating a generalized effect of power training in persons post stroke
74 3.3.2. Identification of Responders and Non responders Although SSWS improved significantly overall, the mean effect was modest with notable variability characteristic of persons post stroke. We performed a secondary analysis to identify responders (RES) and non responders ( N RES) and investigate whether these patterns of response result from subject specific characteristics or attributes of the therapeut ic intervention. Responders were identified as individuals who se improve ment in SSWS exceeded a minimal important difference (MID) and was retained this improvement at completion of both stages of the intervention T he MID is a distribution based measure quantified as one half of the sample standard deviation at baseline 131 Thirty two individuals completed all stage s of the intervention (Figure 3 1 ) and were classified as RES if they achieved 1MID (0.123m/s) increase in SSWS post intervention This approach revealed 15 RES and 17 NRES Demographics and clinical characteristics for RES and NRES are presented in Table 3 1. Both RES ( 0.21 m/s p =0.001) and NRES ( 0.06m/s p<0.001) revealed significant improve ments in SSWS from BAS to GAIT. A s shown in Figure 3 4 and Table 3 2 change s in walking speed w ere significantly greater in RES (p=.001) Importantly, these improvements represent clin ically important change (i.e., 0.16m/s 179 ) only in RES. 3.3.3. Baseline Differences between Responders and Non responders Having defined RES and NRES on the basis of clinically important changes in SSWS, we investigated the contribution of spatiotemporal gait parameters. Significant baseline differences between RES and NRES groups were revealed for : age (RES=55.3010.19, NRES=67.048.69 yrs, p=0.001), PDLS1 (RES=22.545.53, NRES=16.735.47 %GC, p=0.012) and NP knee extensor strength
75 (RES=140.73 23.06, NRES=107.3427.96, p=0.004). All other clinical, spatiotemporal and strength measures were similar between RES and NRES at baseline. Details can be seen in Table 3 1, Table 3 3 and Table 3 4. 3.3.4. Changes in Outcome Measure s : RES vs. NRES 22.214.171.124. Clinical assessments T hree clinical measures: BBS, TUG and 6MWT revealed significant improvements in RES. In NRES significant improvements were detected in: FMA, FMA synergy subscale, BBS and TUG (Table 3 5). I mpro vements in the BBS (p=0.799) and TUG (p=0.247) were comparable between RES and NRES 126.96.36.199. Spatiotemporal p arameters RES revealed significant improvements for all spatiotemporal parameters while NRESs revealed improve ments for all spatiotemporal measur es except PDLS1 and NP step length. In RES, c hanges were significantly greater than NRES for all spatiotemporal measures except PDLS2. A s shown in Figure 3 5 the percentage of individuals who achieved clinically meaningful improvement s were significantly greater among RES for all spatiotemporal measures except PSLS and PDLS2 ( p value s reported in Table 3 3 ) 188.8.131.52. Isometric strength R ES showed a significant improvement in isometric strength for the P knee extensors, whereas N RES significantly improved s trength in P knee extensors, knee flexors, hip abductors and hip flexors. However due to large variability in strength responses differences between groups did not reach statistical significance Moreover, no significant difference for the number of indiv iduals who improved their strength by more than 1 MID was observed between RES s and the NRESs. For detailed descriptive
76 statistics and p values please refer Table 3 4. Although, the absolute changes were not statistically significantly different between RE S and NRES a pattern with greater changes and higher number of individuals improving in proximal hip flexor and hip abductor muscles in the NRES group as opposed to distal muscle of ankle in the RES group was observed, as seen in F igure 3 6 3.4. Discussi on 3.4.1. Differential Effects of Training and Mode of Strength Training Our results reveal significant improvements in walking speed following both power and gait training. I mprovement s for the two training modalitie s were generally comparable (BAS POW an d POW GAIT) indicating no differential effect of training on our primary outcome measure of gait speed. Previous studies reveal both improvement 74 75 82 84 86 or no change 76 83 in gait speed following strength training leaving the question of functional benefits of strengthening unresolved As noted by Patten et al., rather than reflecting failure to induce significant, physiologically important adaptations 72 failure to demonstrate consistent benefits of strength training may result from the heterogeneity among the hemiplegic individuals comprising the study sample.. Although, strength training and gait training have been frequently studied few studies have compared the eff icacy of strength training and gait training for improvin g walking function post stroke. Alth ough, they did not compare the two treatments, a study by Dean et al. 75 investigated t he eff icacy of circuit training which included both strength training and components equivalent to our clinic based gait training ( e.g., walking on treadmill, walking over various surfaces and obstacles walking over slopes and stairs). F ollowing training t hey reported improvement s in walking speed, without assistive
77 devices ranging from 0.032 to 0.212 m/sec. This supports the view t hat strength training can significantly augment the effects of traditional rehabilitation after stroke. Contrary to expectation both concentrically and eccentrically trained individuals show ed comparable improvements in SSWS across all phases of the inte rvention. Our results are consistent with those of Engradt et al. with equivalent improvements in walking speed for both the concentrically and eccentrically trained group s. H owever, they did show differential effects between concentric and eccentric train ing for other parameters, with an increase in the eccentric and the concentric strength in the paretic leg relative to that of the nonparetic leg and an improved symmetry in body weight distribution on the legs while rising from a sitting position for the eccentrically trained group 180 Another study by Clark et al. also sho wed differential effect of concentric versus eccentric training post stroke with eccentrically trained group showing larger improvements in power and neuromuscular activation of knee extensors for both the trained paretic and untrained non paretic leg 181 Consequently, even though gait speed is a widely used measure of walking function, it is not be able to capture the biomechanical and physiological changes occurring as a result of an intervention and hence sh ould be accompanied with other variables more sensitive to changes indicating 3.4.2. Responder s and Non responder s It is well known that physical manifestations of stroke are heterogeneous making it difficult to understand the effects of treatment for each individual and unreasonable to expect results of similar magnitude among individuals treated with a particular therapy 116 117 Different factors such as chronicity of injury, the severity of motor impairment, gait dysfunction and the intensity and duration of the treatment provided
78 contribute to the variability of gains in walking ability observed in many intervention studies 11 8 T his heterogeneity stems from evaluating the combined effects of RES and NRES and limits the ability to determine true treatment efficacy. I n his 1990 review on stroke rehabilitation Erns t expressed a n urgent need to design well planned clinical trials aimed at finding the best approach and discriminating potential responders 119 Although, many studies have been conducted to understand the eff icacy of various treatment approaches, until recently these efforts have not focused on identifying differentiating RES and NRES Mulroy et al. 1 20 attempted to identify gait parameters associated with improved walking speed after body weight supported treadmill training (BWSTT). Individuals who increased SSWS by more than 0.08m/s were identified as high response and revealed greater increase s in hip extension angle and hip flexion power in terminal stance as well as higher intensity of soleus muscle EMG activity during walking. Another study by Bowden et al. 121 attempted to identify the descriptive, clinical measures associated with individuals who respond with clinically meaningful changes in walking speed after locomotor training. Individuals who improved walking speed by more than 0.16m/s were identified as responders and showed significant gains in variable s consistent with motor control, balance, functional walking ability and endurance. We attempted to address this question of potential responders by identifyin g RES and NRES based on clinically important and minimally detectable difference s in SSWS after the complete staged intervention. RES achieved an average improvement of 0.21m/s in SSWS In contrast while NRES demonstrated statistically significant improve ments of 0.06m/s in SSWS th is change fails to reach a level of clinical importance These distinct patterns of behavioral response suggest intrinsic, as yet
79 unidentified physiological difference(s) in the capacity for motor recovery post stroke Our secon dary aim with this study was to understand the characteristics of responders and non responders. 3.4.3. Baseline Differences between Responders and Non responders R ES and N RES revealed equivalent walking speeds at baseline and with the exception of age an d PDLS1, none of the measures differentiated RES at baseline. While a ge is an important factor potentially affecting recovery post stroke 182 183 data from t he Copenhagen Stroke Study indica te that age influences initial stroke severity and ADL recovery but may not influence neurological recovery. This may suggest that older individuals experience more severe stroke s and may have poor compensatory ability H owever, they may have the same capa city for neurological recovery as younger stroke individuals 184 A r ecent study by Bowden et al. evaluated responders and non responders also show baseline difference between t heir groups with respect to age with responders being older 121 whereas the study by Mul r oy et al. show no significant diff erence between the high response and low response group with respect to age 120 This ambiguity in the effect of age on responsiveness to intervention in addition to there being no clear demarcation between the ages of RESs and NRE Ss leads us to believe that this finding may be spurious and age may not be a true predictor of individuals who may respond to treatment. The only spatiotemporal parameter that differed between RES and NRES at baseline was the first p aretic double limb su pport PDLS1 occurs when the paretic leg accepts load after initial contact while the nonparetic leg concurrently pushes off the ground before toe off Accordingly, the PDLS1 parameter reflect s inter limb coupling which may be important to differentiatio n between RES and NRES. In addition, lower
80 PDLS1 may indicate better weight acceptance by RES Notably, baseline equivalence in this sample as determine by clinical scores reveals a significant limitation of existing clinical assessments for predicting tre atment response. 3.4.4. Changes in Clinical Outcome Measure s : Responders vs. Non responders M ultiple factors were responsible for the improve d SSWS in RES. Moreover, s ignificant improvements were seen in clinical measures of balance (BBS), functional walki ng ability (TUG) and endurance (6MWT). While NRES did not show a meaningful improvement in SSWS they also showed improvement s in clinical measures of motor control (FMA, FMA synergy), balance (BBS) and functional walking ability (TUG). I mprovements in TUG and BBS were however, comparable between the two groups sug gesting a more generic form of functional improvement Taken together, these results and our baseline comparisons, confirm that no clinical variables explain improve d SSWS in RES. Therefore, t o f urther elucidate the underlying biomechanical predictors for improved SSWS in RES we studied changes in the spatiotemporal measures. While RES showed significant ly greater improvement in all spatiotemporal measures NRES failed to improve PDLS1 and NP step length Moreover, a significantly greater percentage of R ES achieved clinically meaningful improvement s for all the spatiotemporal measures except PSLS and PDLS2. Hence baseline difference s in PDLS1 between RES and NRES and greater improvement in PDLS1 f or RES may indicate that better weight acceptance on the P side and unloading on the NP side contribute to greater improvement s in SSWS for RES. Future research using detailed biomechanical analyses including ground reaction forces and muscle activity duri ng the double limb support phases is needed to investigate this further.
81 The isometric strength data revealed an interesting pattern. R ES showed significant improvement in P knee extensor strength whereas NRES significantly improved strength for P knee e xtensors, knee flexors, hip flexors and hip abductors. While changes in isometric strength did not differ, statistically, between groups there was an observable pattern with larger changes occurring in proximal muscles in a greater number of NRES and large r changes in distal muscles in a greater number of RES This pattern of greater improvement in the distal muscles in RES suggests sparing of corticospinal tract function in these individuals, retaining their capacity to produce greater power in the distal muscles. Identifying responders to an intervention and understanding their characteristics may be vital in making sound clinical judgments regarding the best treatment approach for most effective rehabilitation post stroke. Future analysis should focus on identifying key kinematic and kinetic parameters to understand the mechanism of response and to reveal underlying biomechanical predictor s of the greater improvements seen in walking speed for responders.
82 Table 3 1. Demographics f or the whole cohort, re sponders, non responders, concentric and eccentric group. C haracteristics Hemiparetic (n=35) Concentric (n=17) Eccentric (n=18) CON vs. ECC at baseline Responders (n=15) Non responders (n=17) RES vs. NRES at baseline Mean age, yr ( SD) 61.7 ( 10.6) 60. 13( 10.8) 63.22 ( 10.6) 0.832 55.3 ( 10.2) 67.05 ( 8.7) 0.001 Gender Male 26 4 4 1.000 12 12 0.402 Female 9 13 14 3 5 Time since stroke onset, mo ( SD) 13.2 ( 4.7) 13.04 ( 4.7) 13.25 ( 4.86) 0.660 13.2 ( 5.9) 12.7 ( 3.7) 1.000 Side affected Right 13 13 9 0.164 5 8 0.491 Left 22 4 9 10 9 Assistive device Yes 22 5 6 1.000 7 12 0.454 No 13 11 11 8 5 Berg Balance Scale (/56) Mean ( SD) 42.8 ( 6.3) 43.06 ( 6.6) 42.56 ( 6.26) 0.798 45.1 ( 4.9) 41.2( 7.1) 0.176 Range 30 53 31 53 30 52 34 53 30 52 Total Fugl Meyer score (/100) Mean ( SD) 79.03 ( 8.5) 80.94 ( 7.1) 77.33 ( 9.4) 0.347 79.3 ( 8.3) 79.3 ( 8.9) 0 .852 Range 58 91 66 91 58 90 59 91 58 91 Fugl Meyer synergy score (/22) Mean ( SD) 15.3 ( 4.3) 16.69 ( 3.2) 14.11 ( 4.9) 0.081 15.5 ( 4.2) 15.2 ( 4.8) 0.882 Range 3 21 8 21 3 19 3 21 3 21
83 Tab le 3 1. Continued C haracteristics Hemiparetic (n=35) Concentric (n=17) Eccentric (n=18) CON vs. ECC at baseline Responders (n=15) Non responders (n=17) RES vs. NRES at baselin e European stroke scale (/100) Mean ( SD) 71.4 ( 11.7) 71.4 ( 11. 8) 71.39 ( 11.97) 0.735 70.8 ( 11.7) 72.2( 12.8) 0.654 Range 46 93 54 93 46 93 46 93 50 93 Functional independence measure (/91) Mean ( SD) 81.7 ( 6.3) 82.5 ( 6.7) 80.94 ( 5.9) 0.423 82.36 ( 6.1) 81.9( 6.5) 0.9 53 Range 68 91 68 91 72 91 72 91 68 91 Six minute walk test (m) Mean ( SD) 207.7 ( 117.8) 222.17 ( 129.7) 194.08 ( 107.6) 0.557 220.5 ( 108.3) 194.7( 134.02) 0.338 Range 59 435.6 66.9 435.6 59 430 66.9 428.3 59 435.6 Timed up and go test (sec) Mean ( SD) 45.1 ( 4.9) 27.43 ( 14.9) 27.74 ( 14.5) 0.845 24.5( 12.6) 31.6( 16.07) 0.264 Range 8.6 56 8.6 55.4 10.5 56 10.3 52 8.6 56 Self selected walking speed (m/ s) Mean ( SD) 0.43 ( 0.25) 0.48 ( 0.29) 0.39 ( 0.19) 0.369 0.45 ( 0.24) 0.39 ( 0.23) 0.261 Functional Classification High (FM 11 6 5 0.725 5 6 1.000 Low ( FM synergy score < 18) 24 11 13 10 11 Training classification Eccentric 18 NA NA 8 9 1.000 Concentric 17 NA NA 7 8
84 Table 3 2 Descriptive statistics for walking speed a nd changes in walking speed for the whole cohort and by group Wilcoxon sign rank test Wilc oxon sign rank test for changes in gait speed from BAS POW and POW GAIT Variable Mean Std Dev Min Max Range Median 95% CI p value p value Overa ll Cohort Velocity_Baseline 0.434 0.247 0.111 0.994 0.883 0.358 (0.35, 0.52) Velocity_PostPower 0.498 0.252 0.150 1.008 0.859 0.419 (0.41, 0.59) Velocity_PostGait 0.553 0.289 0.146 1.223 1.077 0.533 (0.49, 0.66) Change in walkin g speed from baseline to post power training 0.081 0.086 0.150 0.230 0.380 0.078 (.05,.11) <.0001 0.654 Difference in walking speed between power and gait training 0.061 0.091 0.110 0.270 0.380 0.061 (.03,.09) 0.001 Change in walking speed from bas eline to post gait training 0.134 0.095 0.000 0.400 0.400 0.115 (.1,.17) <.0001 Power Training Mode Velocity _Baseline C oncentric 0.485 0.290 0.111 0.994 0.883 0.358 (0.34, 0.63) 0.369 E ccentric 0.386 0.193 0.136 0.752 0.616 0.306 (0.29, 0.48) Change in walking speed from baseline to post power training C oncentric 0.083 0.077 0.034 0.225 0.258 0.068 (0.042, 0.124) 0.852 E ccentric 0.078 0.095 0.150 0.228 0.378 0.078 (0.031, 0.125)
85 Table 3 2. Continued Wilcoxon sign rank test Wilcoxon sign rank test for changes in gait speed from BAS POW and POW GAIT Variable Mean Std Dev Min Max Range Median 95% CI p value p value Power Training Mode Change in walking speed from post power to post gait training C oncentric 0.06 1 0.083 0.082 0.215 0.296 0.047 (0.015, 0.107) 0.941 E ccentric 0.060 0.099 0.111 0.267 0.377 0.082 (0.009, 0.111) Change in walking speed from baseline to post gait training C oncentric 0.138 0.115 0.006 0.398 0.391 0.099 (0.074, 0.201) 0.655 E ccentric 0.130 0.076 0.001 0.279 0.279 0.117 (0.091, 0.169) Responders vs. Non responders Velocity_Baseline Non responder 0.390 0.234 0.136 0.839 0.703 0.245 (0.27, 0.51) 0.261 Responder 0.452 0.244 0.111 0.907 0.796 0.358 (0.32, 0.59) Chang e in walking speed from baseline to post power training Non responder 0.043 0.081 0.150 0.224 0.375 0.028 (0.001, 0.084) 0.018 Responder 0.108 0.072 0.003 0.228 0.231 0.115 (0.068, 0.148) Difference in walking speed between power and gait training Non responder 0.020 0.086 0.111 0.267 0.377 0.004 ( 0.024, 0.065) 0.001 Responder 0.106 0.075 0.078 0.215 0.293 0.120 (0.065, 0.147) Change in walking speed from baseline to post gait training Non responder 0.063 0.037 0.001 0.117 0.117 0.064 (0.044, 0.082) 0.001 Responder 0.214 0.073 0.137 0.398 0.261 0.191 (0.174, 0.254)
86 Table 3 3. Descriptiv e statistics for spatiotemporal parameters and changes in spatiotemporal variables by group post intervention At baseline Change post interve ntion % Change post intervention Percentage responders Mean SD p value Mean SD 95% CI p value p value % p value Spatiotemporal parameters Cadence RES 69.72 18.54 0.481 13.02 9.88 (6.38, 19.66) 0.004 0.013 23.26 63.6 0.002 NRES 63.50 19.44 4.12 3.91 (2.04, 6.20) 0.003 7.55 6.3 Stride length RES 0.61 0.17 0.716 0.21 0.09 (0.15, 0.27) 0.003 < 0.001 35.27 90.9 < 0.001 NRES 0.68 0.25 0.06 0.06 (0.03, 0.09) 0.002 9.81 18.8 Paretic single limb stance RES 20.82 5.52 0.716 5. 03 2.72 (3.20, 6.86) 0.003 0.034 28.35 54.5 0.264 NRES 20.24 7.44 1.98 3.10 (0.33, 3.63) 0.02 10.8 31.3 Non paretic step length RES 0.29 0.11 0.577 0.12 0.08 (0.06. 0.17) 0.006 < 0.001 42.85 90.9 < 0.001 NRES 0.29 0.14 0.02 0.03 ( 0. 002, 0.03) 0.134 3.53 6.3 1st paretic double limb support RES 22.54 5.53 0.009 4.91 4.08 ( 7.65, 2.17) 0.003 0.007 20.93 54.5 0.033 NRES 16.73 5.47 1.05 2.48 ( 2.37, 0.28) 0.134 4.76 12.5 2nd paretic double limb support RES 25.55 7. 72 0.440 4.43 5.01 ( 7.79, 1.07) 0.008 0.422 16.13 18.2 0.549 NRES 33.94 15.34 2.26 3.70 ( 4.24, 0.03) 0.03 7.62 6.3
87 Table 3 4. Descriptive statistics for isometric strength and changes in isometric strength by group post intervention At baseline % Change post intervention Change post intervention Percentage responders Mean SD p value Mean SD p value p value % p value Isometric strength Paretic leg Hip abductors RES 21.96 7.45 0.601 8.72 41.28 0.753 0.213 16.67 0.120 NRES 20.59 15.43 130.52 236.25 0.028 58.33 Hip flexors RES 47.14 24.34 0.351 11.59 31.84 0.249 0.101 30.77 0.254 NRES 40.5 23.10 115.45 314.90 0.001 50.00 Knee extensors RES 64.93 22.45 0.413 21.52 35.42 0.071 0.867 33.33 0.6 60 NRES 59.66 29.07 21.19 26.09 0.004 33.33 Knee flexors RES 16.23 12.47 0.413 113.3 304.04 0.117 0.3 50.00 0.585 NRES 19.36 10.72 45.06 54.28 0.005 46.67 Ankle dorsiflexors RES 18.91 23.11 0.793 53.28 83.01 0.133 0.311 30.7 7 0.161 NRES 12.25 9.01 44.17 128.88 0.249 7.69 Ankle plantarflexors RES 25.21 22.38 0.232 214.92 348.41 0.508 0.722 60.00 0.206 NRES 35.33 17.49 30.74 50.94 0.182 33.33 Composite strength RES 695.68 857.17 0.679 NRES 207.16 225.14 Non paretic leg Knee extensors RES 140.73 23.06 0.004 9.15 20.36 0.209 0.879 16.67 0.367 NRES 107.34 27.96 5.59 19.26 0.055 5.88 Knee flexors RES 52.19 11.25 0.509 15.39 29.12 0.117 0.152 58.33 0.065 NRES 48. 56 15.18 5.24 18.34 0.356 23.53
88 Table 3 5. Descriptive statistics for clinical scores at baseline and following intervention Baseline Post intervention Wilcoxon Rank Sum Test Mean S.D Mean S.D p value FMA CON 81.00 7.65 83.14 7.23 0. 122 ECC 77.88 9.36 81.53 7.67 0.011 NRES 79.29 8.94 83.35 6.69 0.005 RES 79.29 8.59 80.93 8.22 0.265 FMA synergy CON 16.73 3.26 16.93 3.79 0.653 ECC 14.06 5.02 15.47 4.50 0.058 NRES 15.18 4.77 17.00 3.59 0.005 RES 15.47 4.17 15.20 4.71 0.972 ESS CON 71.64 12.18 74.14 11.95 0.126 ECC 71.41 12.34 69.94 18.53 0.516 NRES 72.19 12.76 71.56 17.30 0.244 RES 70.80 11.68 72.13 14.62 0.344 FIM CON 83.86 5.71 83.14 6.29 0.087 ECC 81.44 5.68 83.75 4.60 0.003 NRES 82.75 5.57 83.81 4.82 0.221 R ES 82.36 6.11 83.07 6.08 0.215 BBS CON 43.57 6.86 47.36 5.40 0.001 ECC 42.65 6.44 46.41 5.29 0.001 NRES 41.18 7.14 45.12 5.71 0.001 RES 45.36 5.05 48.93 3.93 0.003 TUG CON 27.64 15.35 22.05 9.46 0.011 ECC 28.57 14.57 24.94 12.88 0.034 NRES 31.5 6 16.07 25.45 10.95 0.011 RES 24.46 12.61 21.51 11.61 0.020 6MWT CON 225.98 133.34 266.82 155.39 0.002 ECC 189.51 109.42 194.14 99.43 0.301 NRES 194.69 134.02 206.40 145.93 0.179 RES 220.46 108.31 253.75 116.63 0.011
89 Figure 3 1. Consort dia gram of participant progression through the trial
90 Figure 3 2. Exercise prescription showing the progression for the lower extremity power training.
91 Photo(s) courtesy of Shilpa Patil Sharma Figure 3 3 .Shows the positioning and the custom attach ments for p ower training and strength testing for A) hip abduction movement and B) a combined lower extremity movement involving hip flexion, knee flexion and ankle dorsiflexion.
92 *Errors represented as 1 Standard error of mea n Figure 3 4 Mean w alking speed at baseline and following intervention s and changes in walking speed following gait training for the whole cohort and responder, non responder, concentric and eccentric groups. A) Mean walking velocity for the overall cohor t, for individuals trained either concentrically or eccentrically and individuals identified as RES or NRES. The light blue shaded area represents the average velocity 1 S.D for controls walking at thei r self selected walking speed. B) Mean change in ave rage velocity for overall cohort, individuals trained either concentrically or eccentrically and individuals identified as RES and individuals identified as NRES from baseline to post POW, post POW to post GAIT and baseline to post GAIT training. The dotte d line represents change of 1MID used to identify RES and NRES. Abbreviations: SSWS, self selected walking speed, CON, concentric, ECC, eccentric, RES, responder, NRES, non responders, BAS, baseline, POW, post power training, GAIT, post gait training, MID, minimal important difference.
93 Figure 3 5. Mean value and changes in spatiotemporal parameters at baseline and following intervention s for the whole cohort, responders, and non responders (A) shows the average value for all the spatiotemporal measures at BAS, post POW and post GAIT training for the overall cohort and for individuals identified as RES or NRES The light blue shaded area represents the average velocity 1 S.D for controls walking at their self selected walking speed. (B) Average change in e ach spatiotemporal measure for the overall cohort, individuals identified as RES and individuals identified as NRES from baseline to post GAIT training. The dotted line represents change of 1MID for each of the spatiotemporal measure. (C) Percentage indivi dual who responded by showing an improvement of 1 MID for each spatiotemporal measure from baseline to post GAIT training for the overall cohort, individuals identified as RES and individuals identified as NRES. Abbreviations: RES, responder, NRES, non res ponders, MID, minimal important difference.
94 *Errors represented as 1 Standard error of mean
95 Figure 3 6 Mean value and changes in strength measures for the paretic leg at baseline and following interventions for the whole c ohort, responders, and non responders (A) Average isometric strength (Nm) of each muscle group for both the RESs and the NRESs at baseline on the paretic side. (B) Mean percentage change for the composite lower extremity score on the paretic side for both RES and NRES. Composite scores were calculated as the sum of the percent strength change of all 6 muscle groups. (C) Mean percentage change for the isometric strength of each muscle group for both the RESs and the NRESs. (D) Percentage of individual respon ding for each muscle group for both the RESs and the NRESs as shown by an improvement of more than 1 MID in their isometric strength after complete staged intervention. 1MID calculated as of standard deviation. Abbreviations: HF, hip flexors, HA, hip ab ductors, KE, knee extensors, KF, knee flexors, DF, ankle dorsiflexors, PF, ankle plantarflexors, RESs, responders, NRESs, non responders, MID, minimal important difference.
96 *Errors represented as 1 Standard error of mean
97 C HAPTER 4 BIOMECHANICAL PROFILE: RESPONDERS VS. NON RESPONDERS 4.1. Background Identifying the best intervention for rehabilitation of stroke individuals is difficult because of the multiple variables that affect the selection and the outcome of these thera peutic measures 185 Consequently, a need for accurate and reliable predictors of functional recovery has been documented because of the marked heterogeneity in stroke manifestation and recovery and the expensive nature of stroke rehabilitation 116 Moreover, one of the predictors believed to affect the accuracy of these predictions is the differences in patient characteristics 116 186 This heterogeneity amon g the stroke population could result in potential responders and non responders to therapy. Hence there is a urgent need to develop well planned clinical trials aimed at discriminating potential responders from non responders in addition to finding the bes t treatment approach 119 Although, significant effort s have been made to understand and investigate various treatment approaches, no effort was made to study the characteristics of potential responders until recently 120 121 In 2010, Mulroy et al. looked at the biomechanical gait parameters associated with responsiveness to body weight supported treadmill training (BWSTT) and to identify the characteristics of partici pants responsive to the treatment. High response group was identified as individuals who showed an improvement of greater than 0.08m/s in their self selected walking speed (SSWS). High response group also showed greater increases in paretic terminal stance hip extension, hip flexion power, peak ankle plantar flexion angle during initial double limb support and intensity of soleus muscle electromyographic (EMG) activity during walking. However, no baseline differences
98 were observed between the high response and the low response group except for the lower extremity F ugl M eyer motor scale (FMA) with significantly higher score in high response group. Another 2012 study by Bowden et al. did similar investigation to study the responders and non responders followi ng a 12 week locomotor intervention incorporating BWSTT with manual trainers accompanied by training overground walking. Responders in this study were identified based on a clinically meaningful increment of more than 0.16m/s in their SSWS post interventio n. They found that the increase in walking speed for the responders was attributed to increases in measures of motor control, dynamic balance and an increase in their cardiovascular capacity and endurance. However, baseline differences between the responde r and the non responder were found only for age (responders older than non responders), FMA and the synergy subsection of FMA scale that examines the ability to perform voluntary isolated movement independent from mass patter ns of whole limb co activation with higher score for responders Consequently, the current literature, although provides important pieces of information regarding the characteristics of responders and the biomechanical contributors to the greater increase in walking speed for responder have some inherent limitations. Bowden et al., although shows some clinical scales for motor control, dynamic balance and endurance could be responsible for the greater improvements in walking speed fail to shed any light on measures such as spatiotempor al, kinematic and kinetic factors contributing to the increased walking speed which could help to elucidate underlying biomechanical predictors for potential responders. On the other hand,
99 although Mulroy et al. did examine the kinematic and kinetic parame ters associated with higher gains in walking speed in the high response group, they only looked at the parameters in the sagittal plane and included only the gait parameters for the paretic side. Moreover, their high response and low response dichotomizati on was based on minimal detectable change and does not necessarily reflect a meaningful change in the wa lking speed. In C hapter 3 of this dissertation, we also investigated the characteristics of responders and non responders after a staged intervention of 5 weeks of progressive power training for the paretic side followed by 3 weeks of clinic based gait training. We defined o u r responders based on an improvement of greater than 0.123m/s. Our criteria of 0.123m/s was based on the concept of minimal importan t difference and was calculated as half of standard deviation at baseline for the SSWS. Our results showed that the only difference s between the responders and the non responders at baseline were for age (non responder older than responder), the initial do uble limb support for paretic leg (paretic loading) and the non paretic isometric knee extensor strength. However, all the other demographic participant characteristics (severity, time since stroke, assistive device), clinical scores, spatiotemporal and is ometric strength measures failed to predict responders. The aim of this study is to investigate the biomechanical attributes including the kinematics and the kinetics contributing to the greater increment in walking speed in responders and the baseline bi omechanical characteristics which may be able t o predict responders and hence indicate a better prognosis after treatment.
100 4.2. Methods 4.2.1. Study Design Participants post stroke underwent a staged intervention involving 5 weeks (15 sessions) of unilate ral paretic limb power training followed by 3 weeks (9 sessions) of clinic based gait training. During the power training stage, participants were randomized to either concentric or eccentric power training. Figure 4 1 illustrates the flow of participants through all stages of the study. (Consort diagram) However, for this study we were only interested in looking at the results after the complete 8 weeks of staged interv ention. In our previous study (C hapter3) it was found that individuals improved their self selected walking speed (SSWS) significantly after the staged intervention with two distinct patterns of response, individuals who improved their SSWS by > 1.23m/s (Responders) and those who were less responsive (Non responders). The cut off speed of 1 .23m/s was based on an improvement of 1 minimal important difference (MID), after the complete 8 weeks of staged interventi on which is defined as half of standard deviation for walking speed at baseline 13 1 An exploratory instrumented gait analysis to examine the biomechanical contributo rs to the increase in SSWS for r esponders and to understand the baseline kinematic and kinetic attributes of the r esponders which may explain the greater improvement in the SSWS for these individuals was conducted at the VA Rehabilitation Research and Development Center; Palo Alto ; CA Participants were recruited from local hospitals, rehabilitation centers, and stroke associations. All procedures were approved by the Stanfo rd University panels on human subjects research and all participants provided written, informed consent prior to study involvement.
101 4.2.2. Participants Thirty two participants (19 left hemiparesis; 24 men; age: 61.54 11.02 years; 12.94 4.77 months post stroke) participated in an 8 weeks staged intervention. They were categorized as either Responders (n = 15; 10 left hemiparesis; 12 men; age: 55.3 10.2 years; 13.2 5.9 months post stroke) or Non responders (n =17; 9 left hemiparesis; 12 men; age: 67.0 5 8.7 years; 12.7 3.7 months post stroke) based on the change in their SSWS post intervention. Inclusion criteria were: hemiparesis resulting from a single cortical or subcortical stroke (confirmed by CT or MRI), between 6 18 months prior to the study, who were categorized as at least unlimited household ambulators (e.g. > 0.3 m/s) 122 and were able to walk at least 10 m indep endently with or without an assistive device participated. Exclusion criteria included: 1) unstable cardiovascular, orthopedic, or neurologic conditions, 2) uncontrolled diabetes that would preclude exercise of moderate intensity, or 3) significant impairm ent affecting the ability to follow directions. Control data were collected for 10 healthy volunteers (6 male; 42.7 11.03 years) having no history of neurologic or orthopedic problems that could impair walking function. 4.2.3. Intervention Subjects par ticipated in an 8 weeks staged intervention with 5 weeks (15 sessions) of paretic limb progressive power training followed by 3 weeks (9 sessions) of clinic based gait training. The lower extremity resistance training was performed three days a week using a Biodex System 3 Pro isokinetic dynamometer (Biodex Medical Systems Inc., Shirley NY) for the paretic leg. Following muscle groups were trained: ankle dorsiflexors and plantarflexors, knee extensors and flexors, hip abductors and a
102 multi segmental task i nvolving hip flexion/extension, knee extension/flexion and ankle plantar/dorsiflexion engaging all these muscle groups together as in walking. Whereas, clinic based gait training was performed three days a week with single session lasting 90 min. Each sess ion involved: stretching (15 minutes), activities to target specific components of gait (30 minutes), balance and/or obstacle course (15 minutes) and treadmill walking (30 minutes). The treatments have been previously described in detail in Chapter 2 and 3 4.2.4. Outcome Measures Specific kinematic and kinetic measures at various joints of the lower extremity such as hip, knee and ankle were studied both pre intervention and post intervention. These included specific joint angles, moments and power in bot h sagittal and frontal planes which determine the walking speed and walking pattern of an individual. Motion analysis was performed during walking using a seven camera Qualisys Motion Capture System 1 A modified Cleveland Clinic Marker set including 38 ma rker placements was used to measure motion in six degrees of freedom (three rotations, three translations) for each segment. A minimum of three markers were placed on each segment to determine the position and orientation in a three dimensional space. 8 se gments were defined: Trunk, Pelvis, Right thigh, Left Thigh, Right shank, Left shank, Right foot and Left foot. Twelve additional markers were placed during the static trial were used to determine the joint axis (flexion/extension) for a given joint and we re consequently removed during dynamic walking trials to facilitate unencumbered motion of the subject during walking. Bilateral kinematics and kinetics were captured at 200Hz. 1 Copyright Qualisys Inc., East Windsor, CT USA
103 Ground reaction forces were measured at 200 Hz using three synchronized force pl ates 2 3 positioned in the laboratory gait walkway. Data were collected as the participants with stroke walked at their self selected and fast speeds and the controls walked at their self selected and two or three slower speeds. Participants were instructed the way you usually do, as if no one was watching and you were walking down the he control subjects were asked to walk progressively slower than their self selec ted walking speed. Five or more trials of each speed condition (i.e., self selected and slow speeds) were collected in order to obtain a minimum of three isolated force plate strikes for each foot Subjects wore their usual footwear. Participants with stro ke were asked to walk without their assistive devices and/or AFO if it was safe to do so. 184.108.40.206. Data management Marker data were labeled using Qualysis Track Manager 4 filtered using a second order Butterworth low pass filter (f c =6Hz) and modeled in Vi sual3D 5 using an eight segment inertial model of each subject based on the data collected by Dempster (1955) 160 It consists of an upper trunk (including the mass of the head and arms), pelvis, two thighs, two shanks and two feet (including the mass of the shoes). Analog ground reaction force data were also filtered using a second order Butterworth low pass filter (f c =10Hz) in Visual3D. The marker and ground reaction force data were input into 2 Copyright Bertec Corporation, Columbus, OH, USA, Model no. k81101/Type 4060 10 3 Copyright Advanced Mechanical Technology, Inc., Watertown, MA, USA, Model no. OR6 6 1000 4 Copyright 2011 Qualysis, Gothenburg Sweden 5 Copyright 2010 C Motion, Version 4.00.19, Inc C Motion, Germantown, Maryland
104 the biomechanical model. Joint angles, moments and powers were output from this model and additional analysis was done using custom designed MATLAB 6 programs. Data quality was visually inspected using a custom designed MATLAB program to before they were extracted for further analysis. These quality checks allowed the user to exclude unusable steps where the subject d id not place their entire foot on the force plate. 4.2.5. Data Analysis Non parametric statistics were used to test as the sample size was small. Differences between the responder and non responder groups at baseline were tested using the Mann Whitney U t est and the Wilcoxon signed Rank test was used to compare pre intervention and post intervention values. Since the kinematics and the kinetics depend on the speed of walking, speed matching was done for each individual in the responder and the non respond er group both at baseline and post intervention to form 4 control groups: controls speed matched to responders at baseline (Con Res @ BAS), controls speed matched to non responders at baseline (Con NRes @ BAS), controls speed matched to responders post in tervention (Con RES @ post intervention) and controls speed matched to non responders post intervention (Con NRes @ post intervention). Responders and Non responders were compared to their respective controls at baseline and post intervention using the Man n Whitney U test. 6 MathWorks Inc, Massachusetts, USA
105 4.3. Results The k inematics and kinetics most relevant to the perceived clinical problem of walking dysfunction post stroke were selected for analysis for both the affected and the less affected side. We analyzed either the kinematic or kinetic s of the joint occurring at a particular instant of the gait cycle such as initial contact (IC) or the maximum and minimum values during a phase of gait cycle such as loading response (LR), midstance (MSt), PreSwing (PreSw), terminal stance (TSt) or Swing (Sw). Based on the convention we used, for all sagittal joint angle flexion and DF is positive, for all frontal joint angles adduction is positive and for all transverse joint angles internal rotation is positive. For joint moments we expressed all the extension and PF internal joint moments in sagittal plane as positive and abduction internal joint moment in frontal plane as positive. 4.3.1. Baseline Differences between the Responders and the Non Responders Significant difference were found at base line for the responders and the non responders for the following parameters: peak hip adduction angle during stance for the paretic side (responder = 4.33 3.71, non responder = 7.94 4.26 degrees, p =0.047), peak ankle DF angle during LR for the non par etic side (responder = 1.56 2.64, non responder = 2.62 10.97 degrees, p =0.041) and peak hip abduction moment during stance for the non paretic side (responder = 0.99 0.23, non responder = 0.72 0.2 Nm/kg, p =0.016). Other variables showing a trend towards being significantly different at baseline were peak hip abduction angle during swing for the paretic side (responder = 4.08 3.24, non responder = 1.36 3.58 degrees, p =0.097), hip adduction angle during stance for the paretic side (responder = 1.77 3.11, non responder = 1.23 3.98
106 degrees, p =0.053), peak ankle DF angle during TSt for the non paretic side (responder = 2.44 3.72, non responder = 3.64 11.1 degrees, p =0.053). Figure 4 2 shows the baseline differences between the responde r and non responder groups and the comparison with the speed match controls. Moreover for the peak hip abduction angle during swing for the paretic side and peak hip abduction moment during stance for the non paretic side the responder were not significan tly different than the speed matched controls (Con RES @ BAS) with a p value of 0.123 and 0.971 respectively whereas the non responders were significantly different as compared to the speed matched controls (Con NRES @ BAS) with a p<0.001 and p=0.001 respe ctively. On the other hand the hip adduction angle at stance for the paretic leg and peak ankle DF angle during LR for the non paretic side for the responders as well as the non responders were not different as compared to the Con RES @ BAS and Con NRES @ BAS respectively. However, for all the other variables found to be different at baseline the non responders were comparable to their speed matched controls whereas the responders were significantly different than the speed matched controls at baseline. T he mean and the standard deviation for all the parameters for responders, non responders and their respective speed matched controls are presented in Table 4 1 4.3.2. Changes from Pre Intervention to Post Intervention 220.127.116.11. Joint angles As shown in Fi gure 4 3, responders showed significant increase for peak knee flexion angle during swing for the paretic leg (33.77 12.17 vs. 36.12 12.71 degrees, p = 0.047). However, it was still significantly lower than the speed matched controls. They also showed significant decrease in the knee flexion angle at IC on the non paretic
107 side (9.28 14.73 vs. 4.8 12.49 degrees, p = 0.03) such that they normalized towards speed match controls. There was significant increase in the peak knee flexion angle during pre swing (43.21 5.74 vs. 47.70 8.8 degrees, p=0.044) and swing (55.92 6.97 vs. 60.46 8.36 degrees, p =0.026) on the non paretic side for the non responders moving further away from the speed match controls. Non responders also improved their peak hip adduction angle significantly on the non paretic side (3.43 4.15 vs. 5.54 4.49 degrees, p =0.03) such that they were comparable to the speed matched controls. 18.104.22.168. Internal joint moments Responders showed significant increase for peak hip flexion moment during terminal stance for the paretic leg ( 0.28 0.15 vs. 0.38 0.22 Nm, p = 0.005) and the non paretic leg ( 0.28 0.18 vs. 0.40 0.21 Nm, p = 0.037), peak ankle PF moment for the paretic (0.79 0.34 vs. 0.94 0.36 Nm, p = 0.005) and non paretic leg (1.08 0.24 vs. 1.29 0.29 Nm, p = 0.005). Although, the peak ankle PF moment for the paretic side improved significantly it was still significantly lower than the peak PF moment for the speed match controls. On the other hand, peak hip abd uction moment during stance for the non paretic side (0.99 0.23 vs. 0.847 0.16 Nm, p=0.037) decreased significantly in responders and moved away from control values to become significantly different than Con RES @ post intervention. Although not signif icant it improved on the paretic side (0.59 0.21 vs. 0.72 0.22 Nm, p=0.059) even though it did not reach the normal values. Non responder increased the knee flexion moment at initial contact significantly for the paretic side ( 0.05 0.04 vs. 0.07 0.05 Nm, p = 0.028) although it still remained comparable to the speed matched control. They also improved the peak hip
108 abduction moment during stance for the non paretic side (0.72 0.2 vs. 0.99 0.33 Nm, p = 0.004) such that they were equivalent to the speed match control values post intervention. 22.214.171.124. Joint powers Figure 4 4 shows that responders showed significant increase in the H1 power burst on the paretic side (0.20 0.13 vs. 0.38 0.26 W, p=0.009), the H2 power burst on the non paretic side ( 0.16 0.1 vs. 0.27 0.16 W, p = 0.022), H3 power burst on both the paretic (0.24 0.13 vs. 0.39 0.2 W, p = 0.022) and non paretic side (0.31 0.17 vs. 0.41 0.17 W, p=0.013) and A2 power burst on both the paretic (0.43 0.83 vs. 0.63 1.02 W and the non paretic side s (1.23 0.76 vs. 1.81 1.12 W, p = 0.005). Al though the A2 power increased significantly on the paretic side for the responders it was still significantly lower than the speed matched controls post intervention. On the other hand, non responders increased significantly on the paretic (0.30 0.19 vs. 0.36 0.2 W, p = 0.047) and the non paretic (0.43 0.21 vs. 0.53 0.25 W, p =0.047) side for H1 power burst, on paretic side for the H2 power burst ( 0.08 0.07 vs. 0.186 0 .21 W, p = 0.036), H3 power burst (0.21 0.16 vs. 0.28 0.18 W, p = 0.031), K1 power burst ( 0.23 0.28 vs. 0.36 0.36 W, p = 0.027), K2 power burst (0.17 0.15 vs. 0.26 0.2 W, p = 0.041) and for the K4 power burst ( 0.13 0.14 vs. 0.18 0.15 W, p = 0.015). Although, the H1 on the non paretic side and the K1 on the paretic side increased they shifted further away from the speed match ed control values. Refer to T able 4 1 for details regarding the responder, non responders and the speed match contr ols.
109 4.4. D iscussion 4.4.1. Baseline Differences between the Responders and the Non Responders The baseline differences that were observed between the responders and the non responders were primarily in the frontal plane for the hip joint and the sagittal plane at t he ankle joint. At the hip we observed that the responders were in general more abducted on their paretic side during the whole gait cycle with less adduction at IC and during the stance phase and more abduction during swing as compared to the non responders. Although, the hip adduction angle for the paretic leg at initial contact was less for the responders as compared to the non responders, they were both still comparable to their respective speed matched control. However, responders seem to produce significantly greater amount of internal abduction moment during stance on their non paretic side and a greater hip abduction angle during swing on their paretic side, although it is not statistically significant. As stabilizing the trunk mass over the hip introduces high demand for muscular control in the stance phase and the rapid transfer of body weight onto the loading limb requires active lateral stabilization of the pelvis over the hip especially in the loading response 187 The higher and more normal abd uction moment during stance on the non paretic side and hip abduction angle during swing on the paretic side for the responders may suggest an ability to better stabilize their pelvis during weight transfer on the non paretic side. This finding is in agree ment with the results in C hapter 3 which showed that even though the initial double limb support phase for the NP side was not statistically different at baseline between the responder and the non responders, it was closer to the controls walking at their self selected speed as compared to the non responders (responder= 25.55 7.72 non responders = 33.94 15.34, p = 0.440)
110 4.4.2. Changes from Pre Intervention to Post Intervention The major contribution for energy generation and propulsive force for forwa rd progression comes from 3 power bursts: H1 (concentric activity of hip extensors during 48 Moreover, out of these three power bursts A2 is suppose d to contribute the most (about 75%) tow ards this propulsive force in healthy individuals with H2 and H3 taking care of the rest 188 Impaired powe r generation such as smaller A2 burst has been reported in individuals with stroke and these deficiencies are usually countered by the stronger muscles through inter limb(increase in the power bursts on the less affected side) and intra limb(using hip fl ex compensatory gait patterns 16 Moreover, it has been shown that weakness of the plantar flexors can limit the ability of an individual to increase their walking speed and is usually compensated by the activity of hip flexor muscles in individuals with stroke 49 From the re sults it appears that the responders are using a combination of restitution and inter limb and intra limb compensation to achieve the prominent gain in their walking speed. The increase in the internal hip flexion moment at terminal stance and the accelera tion power burst due to the concentric activity of the hip flexor muscles (H3) to values considerably more than the speed matched controls on both the paretic and the non paretic side of the responders show compensation on both the affected and the less af fected side at the hip to accomplish forward progression. However, there was also a significant improvement in the peak plantarflexion moment and the A2 burst for both legs in the responders which represents the concentric work of the plantarflexors accele rating the stance limb into swing. As they generate a large portion of the energy required to move the limbs forward in the push off phase plantarflexor muscles are
111 considered important in gait speed regulation in healthy individuals 189 Since weakness is usually more pronounced distally on the paretic side in individuals with stroke 53 and the moments and power produced by the plantarflexors depend on walking speed 16 190 plantarf lexor weakness is considered to be a limiting factor in the production of plantarflexion moment and power required to walk fast 49 Although, for responders there was a significant improvement in the PF moment and power on the paretic side it was still significantly lower than the speed match ed controls whereas the moment and the power at the ankle were greater than t he speed match ed control in the non paretic side. Consequently it appears that the responders normalize their PF moment and power at the ankle on the paretic/affected side and compensate at the hip on the paretic side and at the hip and ankle on the non pa retic side. In addition, responders also showed a significant improvement in the H1 power burst on the paretic side caused by the concentric activity of the hip extensors helping to pull the trunk over the hip during loading response. Furthermore, it has been shown that individuals with stroke as compared to speed matched individual s show impairment in swing initiation on the paretic side as shown by a decrease in the leg kinetic energy at toe off or the propulsive forces on of the hip flexors. T his generation of kinetic energy is related kinematically to the peak knee flexion angle during swing 35 The increase in the H3 and A2 power as well as the peak knee flexion angle during swing may suggest that the responders were able to initiate stance to swing better on their paretic side 191
112 On the other hand, non responders only showed significant changes in the energy production at the hip with no changes at the ankle. They significantly improved paretic side. There was also an increase in the positiv e work at the knee on the paretic side as shown by greater K2 caused by the concentric activity of quadr iceps in early stance. Although, these increase s in the propulsive power were also accompani ed by increases in the braking power s at the knee as shown b y an increase in the K1 and K4 power bursts on the paretic side. The A2 power burst did not change post intervention and was still lower than the speed matched controls. Moreover, after improvements post intervention both the H1 and the H3 power at the hip on the paretic side were equivalent to the powers for the speed matched controls. Although, the increase in the braking force produced by the eccentric activity of the hamstring muscles (K4) is within the normal range post intervention, the increase in th e absorption at the knee due to the eccentric activity of the quadriceps during the loading response (K1) was more tha n the speed matched control. I t is possible that this imbalance between the pro pulsive force generation and br aking forces or absorption i s the reason for the limited gain in walking speed for these individuals. In addition, the non responder also improved their peak hip abduction moment during stance significantly on the non paretic side which may have resulted in better paretic peak hip ab duction angle during swing, although not significantly different from baseline. So it is possible that in addition to the increase in the propulsive forces, the non responder may also have improved the lateral stabilization of the trunk over the pelvis dur ing the loading response.
113 Interestingly, most of the changes occurring in the non responders post intervention were located more proximally at the hip whereas the responders show improvement both proximally and distally. 4.5. Limitations Firstly, hip abd uction and adduction angle that we analyzed in this study were a measure of total pelvic femur angle and hence we cannot make separate judgment regarding the thigh motion (thigh displacement from the vertical) or the pelvic motion (arc of pelvic tilt that may add to or subtract from the arc of hip motion). Secondly, because of the small sample sizes in each group and the multitude of variables to be tested, the alpha values for the non param etric Mann Whitney test or Wil co xo n sign test were not corrected fo r multiple tests. However, all the p values a re provided in the t able s allowing the strength of the evidence to be assessed by the authors.
114 Table 4 1 Descriptive statistics for baseline kinematics and kinetics measure and changes in kinematics and kinetics variables from pre to post intervention by group and for speed matched control s At Baseline Test RES vs. NRES at b a selin e Post Intervention Test Pre Post interven tion RES Con RES p value NRES Con NRES p value p value RES Con RES p value NRES Con NRES p valu e RE S NR ES Joint angles SAGITTAL PLANE Hip flexion at IC P 24.552 7.11 35.312 8.29 0.009 24.928 9.59 35.236 5.96 0.004 0.938 26.695 7.68 36.163 5.36 0.001 23.624 13.76 36.119 6.2 0.0 02 0.2 03 0.9 18 NP 33.201 5.19 0.481 30.574 9.4 0.084 0.286 31.919 6.92 0.114 33.498 8.4 0.2 44 0.8 78 0.2 55 Peak hip flexion angle during Sw P 28.78 10.4 37.103 8.66 0.105 28.259 10.48 36.77 6.4 0.027 0.979 31.04 7.52 37.599 6.08 0.032 28.148 13.36 37.616 6.54 0.0 17 0.3 33 0.7 17 NP 37.564 6.57 1.000 34.474 9.38 0.301 0.517 37.28 7.47 0.829 37.883 8.29 1.0 00 0.6 46 0.1 96 Peak hip extension angle during TSt P 6.735 10.93 1.465 6.77 0.315 7.63 9.32 0.967 5.04 0.108 0.897 4.802 8.89 2.145 6.01 0.427 6.217 10.34 2.23 6.02 0.1 34 0.5 75 0.8 36 NP 0.1 9.03 0.631 2.658 8.5 0.301 0.586 3.689 6.14 0.021 0.349 7.88 0.4 87 0.2 03 0.2 34 Knee flexion angle at IC P 4.437 7.31 5.342 3.48 0.971 4.486 4.61 4.856 2 1.000 0.856 6.318 7.49 4.668 3.43 0.399 5.929 7.1 4.589 3.2 0.4 04 0.2 85 0.5 69 NP 9.276 14.73 0.190 10.698 8.06 0.065 0.897 4.799 12.49 0.981 11.847 10.46 0.0 13 0.0 28 0.5 69 Peak knee flexion during PreSw P 25.209 8.39 40.541 6.5 0.000 25. 179 8.8 38.449 5.32 0.000 0.856 26.848 9.02 40.862 6.91 0.000 29.515 9.24 40.208 7.07 0.0 04 0.1 69 0.1 21 NP 44.194 6.36 0.165 43.214 5.74 0.095 0.286 44.217 8.18 0.277 47.703 8.8 0.0 33 0.7 21 0.0 44
115 Table 4 1 Continued At Baseline Test RES vs. NRES at baselin e Post Intervention Test Pre Post interven tion RES Con RES p value NRES Con NRES p value p value RES Con RES p value NRES Con NRES p valu e RE S NR ES Joint angles SAGITTAL PLANE Peak knee flexion angle during S w P 33.766 12.17 55 6.78 0.000 32.772 13 52.746 5.74 0.000 0.979 36.121 13.71 55.459 5.96 0.001 37.685 11.11 54.429 6.77 0.0 01 0.0 47 0.0 79 NP 56.257 7.13 0.481 55.921 6.97 0.095 0.938 56.899 8.74 0.456 60.464 8.36 0.0 47 0. 6 46 0.0 26 Peak knee extension during MSt P 2.173 8.32 6.93 4.09 0.011 0.93 8.08 6.652 2.87 0.017 0.201 0.867 5.79 7.583 4.19 0.004 2.373 10.69 7.295 4.2 0.1 75 0.0 93 0.5 01 NP 2.569 7.12 0.165 4.147 4.31 0.108 0.586 2.689 6.9 0.0 47 6.39 9.15 0.3 53 0.3 33 0.2 78 Ankle DF angle during IC P 6.129 7.36 2.091 3.12 0.247 5.1 7.78 2.794 2.25 1.000 0.979 5.72 7.39 2.699 2.19 0.373 4.325 4.26 3.425 2.43 0.8 90 0.5 75 0.4 08 NP 7.364 5.05 0.043 5.629 11.13 0.452 0.150 5.011 3.47 0.059 4.313 4.02 0.4 87 0.2 03 0.7 96 Peak ankle PF angle during TSt P 3.126 4.74 3.273 2.38 0.529 2.597 7.3 4.358 3.06 0.419 0.979 3.478 4.81 4.547 3.57 0.648 1.987 4.85 3.442 2.33 0.1 75 0.2 41 0.7 17 NP 7.006 5.74 0.089 6.752 12.36 0.718 0.310 4.78 4.26 0.943 5.935 6.48 0.1 47 0.5 08 0.7 96 Peak ankle DF angle during Sw P 0.663 4.16 2.345 2.35 0.089 0.243 7.53 1.574 1.72 1.000 0.660 1.059 5.52 1.196 1.83 0.323 0.527 5.37 1.896 1.91 0.2 64 0.1 14 0.8 36 NP 1.772 4.65 0.029 1.475 12.07 0.934 0.201 0.081 4.63 0.347 0.813 5.22 0.0 82 0.6 46 0.5 69 Peak ankle DF angle during St P 6.085 4.31 8.385 1.91 0.247 6.441 6.58 8.441 1.8 0.357 0.897 5.281 4 .53 7.666 1.71 0.200 7.353 5 8.688 1.82 0.4 58 0.2 85 0.2 55 NP 4.092 3.14 0.002 4.197 10.95 0.169 0.201 6.388 3.88 0.486 6.437 4.01 0.0 15 0.0 74 0.6 42
116 Table 4 1 Continued At Baseline Test RES vs. NRES at baselin e Post Interventi on Test Pre Post interven tion RES Con RES p value NRES Con NRES p value p value RES Con RES p value NRES Con NRES p valu e RE S NR ES Joint angles FRONTAL PLANE Hip add angle at IC P 1.773 3.11 0.237 1.98 0.123 1.233 3.98 0.058 1.62 0.637 0 .053 2.344 2.65 0.313 1.83 0.114 0.156 4.07 0.502 2.04 1.0 00 0.6 46 0.1 21 NP 2.405 3.62 0.063 3.807 7.06 0.207 0.816 1.714 5.74 0.943 2.3 7.56 0.2 25 0.9 59 0.1 21 Peak hip abd angle during Sw P 4.078 3.24 6.172 2.04 0.123 1 .361 3.58 6.479 2.28 0.000 0.097 4.448 2.57 6.266 2.44 0.114 2.643 4.18 5.706 2.56 0.0 59 0.5 75 0.1 21 NP 5.644 3.15 0.353 6.778 6.48 0.890 0.421 5.746 5.28 0.829 5.419 6.77 0.4 87 0.2 03 0.1 63 Peak hip add angle during St P 4.333 3.71 7.459 2.14 0.035 7.943 4.26 7.736 2.2 0.978 0.047 3.995 3.29 7.022 1.71 0.007 6.649 4.26 7.832 2.31 0.3 29 0.5 75 0.1 34 NP 5.523 2.51 0.035 3.427 4.15 0.010 0.121 6.293 4.13 0.486 5.54 4.49 0.1 47 0.5 75 0.0 3 In ternal joint moments SAGITTAL PLANE Peak hip ext moment during LR P 0.343 0.2 0.314 0.11 0.971 0.408 0.16 0.302 0.16 0.155 0.338 0.42 0.22 0.303 0.18 0.167 0.48 0.27 0.334 0.14 0.1 61 0.2 85 0.3 34 NP 0.533 0.2 0.011 0.53 0.23 0.01 2 1.000 0.641 0.21 0.000 0.636 0.22 0.0 01 0.1 39 0.0 53 Peak hip flx moment during TSt P 0.282 0.15 0.254 0.12 0.853 0.226 0.1 0.263 0.07 0.138 0.311 0.382 0.22 0.329 0.11 0.867 0.302 0.19 0.273 0.13 0.8 90 0.0 05 0.1 91 NP 0 .277 0.18 0.912 0.308 0.21 0.682 0.531 0.403 0.21 0.256 0.318 0.19 0.6 77 0.0 37 0.8 65
11 7 Table 4 1 Continued At Baseline Test RES vs. NRES at baselin e Post Intervention Test Pre Post interven tion RES Con RES p value NRES Con NRES p v alue p value RES Con RES p value NRES Con NRES p valu e RE S NR ES Internal joint moments SAGITTAL PLANE Knee extension moment during IC P 0.049 0.04 0.045 0.06 0.888 0.048 0.04 0.02 0.04 0.197 0.643 0.084 0.1 0.079 0.08 0.882 0.074 0. 05 0.034 0.05 0.1 69 0.3 1 0.0 28 NP 0.108 0.04 0.040 0.119 0.07 0.003 0.938 0.189 0.13 0.020 0.142 0.07 0.0 01 0.0 8 0.3 74 Peak knee ext moment during LR P 0.106 0.16 0.209 0.16 0.247 0.062 0.1 0.213 0.19 0.025 0.723 0.173 0 .23 0.338 0.24 0.139 0.096 0.24 0.226 0.2 0.0 91 0.5 75 0.5 32 NP 0.149 0.22 0.739 0.094 0.18 0.174 0.683 0.18 0.23 0.053 0.161 0.23 0.5 78 0.7 21 0.2 56 Peak knee flx moment during PreSw P 0.319 0.23 0.231 0.13 0.631 0.293 0.16 0. 208 0.13 0.194 0.935 0.317 0.2 0.156 0.11 0.032 0.247 0.27 0.192 0.16 1.0 00 0.9 59 0.4 6 NP 0.195 0.14 0.481 0.176 0.18 0.482 0.495 0.151 0.17 0.683 0.117 0.15 0.1 91 0.4 45 0.2 11 Peak ankle PF moment P 0.794 0.34 1.157 0.17 0.007 0.672 0.29 1.17 0.12 0.001 0.261 0.943 0.36 1.21 0.11 0.012 0.731 0.34 1.161 0.13 0.0 04 0.0 05 0.1 12 NP 1.08 0.24 0.436 1.141 0.19 0.815 0.461 1.29 0.29 0.516 1.164 0.34 0.7 11 0.0 05 0.0 88 FRONTAL PLANE Peak Hip abd moment during St P 0.59 0.21 0.968 0.11 0.001 0.609 0.22 0.973 0.09 0.000 0.807 0.722 0.22 0.975 0.09 0.000 0.533 0.31 1.002 0.1 0.0 00 0.0 59 0.1 25 NP 0.99 0.23 0.971 0.716 0.2 0.001 0.016 0.847 0.16 0.025 0.986 0.33 0 .6 43 0.0 37 0.0 04
118 Table 4 1 Continued At Baseline Test RES vs. NRES at baselin e Post Intervention Test Pre Post interven tion RES Con RES p value NRES Con NRES p value p value RES Con RES p value NRES Con NRES p valu e RE S NR ES Joint powers SAG ITTAL PLANE H1 P 0.197 0.13 0.26 0.11 0.211 0.301 0.19 0.305 0.19 0.837 0.144 0.376 0.26 0.275 0.18 0.297 0.36 0.2 0.296 0.18 0.5 25 0.0 09 0.0 47 NP 0.509 0.26 0.028 0.428 0.21 0.210 0.643 0.619 0.38 0.002 0.526 0.25 0.0 25 0.3 3 3 0.0 47 H2 P 0.159 0.16 0.135 0.12 0.842 0.082 0.07 0.129 0.07 0.066 0.261 0.223 0.28 0.193 0.15 0.595 0.186 0.21 0.143 0.13 0.7 51 0.3 86 0.0 36 NP 0.161 0.1 0.497 0.2 0.15 0.332 0.643 0.271 0.16 0.145 0.179 0.1 0.2 87 0.0 22 0.6 09 H3 P 0.239 0.13 0.231 0.13 0.720 0.211 0.16 0.245 0.11 0.298 0.397 0.386 0.2 0.283 0.17 0.193 0.278 0.18 0.217 0.1 0.4 91 0.0 22 0.0 31 NP 0.313 0.17 0.315 0.365 0.19 0.162 0.428 0.41 0.17 0.060 0.368 0.17 0.0 18 0.0 13 0.4 6 K1 P 0.249 0.23 0.138 0.17 0.075 0.225 0.28 0.14 0.12 0.482 0.428 0.308 0.18 0.299 0.33 0.236 0.36 0.36 0.161 0.16 0.0 47 0.0 93 0.0 27 NP 0.209 0.11 0.123 0.319 0.25 0.021 0.397 0.272 0.16 0.300 0.294 0.2 0.0 29 0.7 21 0.7 76 K2 P 0.266 0.28 0.15 0.1 0.481 0.165 0.15 0.14 0.1 0.907 0.311 0.319 0.17 0.18 0.18 0.012 0.257 0.2 0.14 0.1 0.1 11 0.1 39 0.0 41 NP 0.266 0.2 0.105 0.245 0.21 0.238 0.935 0.302 0.18 0.021 0.276 0.19 0. 0 42 0.3 86 0.3 63 K3 P 0.066 0.03 0.125 0.04 0.004 0.064 0.05 0.132 0.04 0.004 0.683 0.123 0.08 0.182 0.07 0.041 0.082 0.07 0.128 0.04 0.0 33 0.1 69 0.3 63 NP 0.168 0.11 0.436 0.146 0.07 0.726 0.765 0.216 0.15 0.905 0. 163 0.06 0.1 61 0.3 33 0.1 25
119 Table 4 1 Continued At Baseline Test RES vs. NRES at baselin e Post Intervention Test Pre Post interven tion RES Con RES p value NRES Con NRES p value p value RES Con RES p value NRES Con NRES p valu e RE S NR ES Join t powers SAGITTAL PLANE K4 P 0.185 0.24 0.221 0.17 0.165 0.133 0.14 0.18 0.11 0.290 0.495 0.296 0.46 0.327 0.28 0.028 0.179 0.15 0.212 0.13 0.4 04 0.0 74 0.0 15 NP 0.571 0.29 0.005 0.581 0.34 0.000 0.892 0.669 0.36 0.00 3 0.573 0.32 0.0 00 0.0 74 0.8 65 A1 P 0.673 0.77 0.503 0.23 0.684 0.403 0.28 0.515 0.24 0.194 0.428 0.74 0.51 0.504 0.2 0.217 0.524 0.44 0.499 0.22 0.6 11 0.1 39 0.0 61 NP 0.668 0.22 0.123 0.79 0.3 0.021 0.261 0.886 0 .38 0.003 0.948 0.6 0.0 25 0.1 39 0.1 73 A2 P 0.426 0.83 0.868 0.49 0.004 0.438 0.45 1 0.45 0.004 0.285 0.628 1.02 1.158 0.6 0.001 0.457 0.55 0.954 0.45 0.0 06 0.0 05 0.6 91 NP 1.228 0.76 0.247 1.232 0.73 0.519 0.935 1.811 1.1 2 0.126 1.344 0.78 0.2 85 0.0 05 0.1 25
120 Figure 4 1. Consort diagram of participant progression through the trial
121 *Errors represented as 1 Standard error of mean Figure 4 2. Represents baseline differences between th e RES and the NRES and between each group and their speed matched controls for joint angles and moments Mean values for selected joint angles and moments are plotted. Gray bars represent the responders while the black bars represent the non responder. Whi te bar represents the speed matched controls for the responder (Con RES) and the non responder (Con NRES) group. Abbreviations: RES, responder, NRES, non responders, PRE, pre intervention, POST, post intervention
122 *Errors repres ented as 1 Standard error of mean Figure 4 3. Represents changes in select joint angles and moments from pre intervention to post intervention for both paretic an d non paretic side of the RESs, NRES s and respective speed matched controls. Mean values for selected joint angles and moments are plotted. Gray bars represent the pre intervention values while the black bars represent values post intervention. Abbreviations: RES, responder, NRES, non responders, PRE, pre intervention, POST, post intervention, Co n RES, speed matched controls for responders and Con NRES, speed matched controls for non responder group.
123 *Errors represented as 1 Standard error of mean Figure 4 4. Represents the changes in select joint power from pre int ervention to post intervention for both paretic and non paretic side for the RES and the NRES and respective speed matched controls. Mean values for selected joint powers are plotted. Gray bars represent the pre intervention values while the black bars rep resent values post intervention. Abbreviations: P, paretic, NP, non paretic, RES, responder, NRES, non responders, PRE, pre intervention, POST, post intervention, Con RES, speed matched controls for responders and Con NRES, speed matched controls for non r esponder group.
124 CHAPTER 5 MECHANISM OF IMPROVEMENT: RESPONDERS VS. NON RESPONDERS 5.1. Background It has long been shown that the physical manifestation of stroke are heterogeneous 116 117 making it unreasonable to expect similar resu lts for all individuals with stroke given a treatment In fact, various factors have been named which may potentially be responsible for the variability of gains in walking ability following treatment such as chronicity of injury, severity of motor impair ments, specific characteristics of gait dysfunction and the intensity and duration of treatment. This heterogeneity among the stroke population may stem from a combination of individuals who respond well to a responder). Even though the demand to urgently design well planned clinical trials aimed at finding the best approach and discriminating potential responders has been expressed more than 2 decades ago 119 it has not been addressed until recently and there are still questions regarding the characteristics of po tential responders as well as the mechanism of walking improvement in potential responder which still remain unanswered. As discussed in our previous chapter s although two recent studies 120 121 have tried to answer these questions, they have either only studied the clinical and behavioral measures 121 and have not taken a look at biomechanical or EMG parameters based on a gain in walking spee d which may not necessarily be meaningful in terms of function 120 In addition this study did not study the differences between the responders and the non responders in terms of these biomechanical attributes at baseline and only
125 l ooked at the differences in subject measure and clinical measures at baseline. Bowden et al. found that only three clinical variables we re different at baseline: age, Fugl M eyer assessment score (FMA) and the synergy subsection of the Fugl M eyer assessment which examines the ability of an individual to perform voluntary isolated movement independent from mass pattern of whole limb co activation (FMA S) with responders older than the non responders and scoring more for FMA and less for FMA S than non respond ers. Mulroy et. al., on the other hand, showed no significant difference between their responder and non responders for age and a significantly higher score for FMA for responders. From our previous study (Chapter 3) although age was significantly differen t between the responders and the non responders with responders younger than non responders, there was no difference at baseline for any of the clinical measures includ ing the FMA and FMA S. These equivocal finding s suggest that age and clinical scores ma y not be the best predictors of responders and that there is a need to explore further. In C hapter 4 we attempted to understand the biomechanical attributes which may predict the responders at baseline or contribute in achieving the higher improvement in walking speed following treatment. Walking is a complex phenomenon and multiple factors and parameters could play a role in developing a walking pattern. On one hand, kinematics such as joint angle may result because of muscle activity and may represent ho w a person is walking, however, on the other hand position of joint and body segment may be able to determine the function a muscle will be able to play given the kinematic state of the leg during walking. Moreover, a d reaction force (GRF) and hence the joint moments and powers responsible for
126 accelerating some body segments or decelerating the other segments. Hence, to get a complete picture it is important that we have al l the pieces of the puzzle. In C hapter 4 we ex amined the joint angles, internal joint moments and power during gait in responder and non responder. Hence, in this study we will examine the GRF data and the electromyographic data (EMG) in order to understand the parameters responsible for the improved moments and power responsible for the higher improvement in walking speed in responders and also GRF and EMG parameters responsible for the difference observed between the responders and the non responders at baseline. Understanding these parameters may he lp us determine if there are underlying neurological difference among the responders and non responders which may be responsible for their varying responses to treatment. 5.2. Methods Subject characteristics, experimental design and i nterventions were pre sented in Chapter 4. Dynamic electromyography (EMG) performed concurrently provides an indirect indicator of muscle activation EMG can be recorded and analyzed to determine the timing and relative intensity of muscular effort. In addition force plate recor dings quantify the functional demands being experienced during the weight bearing period. 5.2.1. Data Collection Motion analysis was performed during walking using a seven camera Qualisys Motion Capture System 1 Ground reaction forces were measured at 2 00 Hz using three synchronized force plates 2 3 positioned in the laboratory gait walkway. Surface 1 Copyright Qualisys Inc., East Windsor, CT USA 2 Copyright Bertec Corporation, Columbus, OH, USA, Model no. k81101/Type 4060 10 3 Copyright Advanced Mechanical Technology, Inc., Watertown, MA, USA, Model no. OR6 6 1000
127 electromyography (EMG) was recorded at 2000Hz for 8 muscles per leg using pre amplified electrodes 4 pl aced over the muscle bellies of: Tibialis A nterior (TA), Me dial Gastrocnemius (MG), Soleus (SOL), Rectus Femoris (RF), Vastus Lateralis (VL), Biceps Femoris (BF), Semitendinosus (SM) and Gluteus Medius (GM). Data were collected as the participants with stroke walked at their self selected speeds and the controls w alked at their self selected and two or three slower speeds. Participants were add ition, t he control subjects were asked to walk progressively slower than their self selected walking speed. Five or more trials of each speed condition (i.e., self selected and slow speeds) were collected in order to obtain a minimum of three isolated forc e plate strikes for each foot Subjects wore their usual footwear. Participants with stroke were asked to walk without their assistive devices and/or AFO if it was safe to do so. 5.2.2. Data Reduction Analog ground reaction force data were filtered using a second order Butterworth low pass filter (f c =10Hz) in Visual3D. Additional analysis was done using custom designed MATLAB 5 programs. EMG data were collected using a separate hardware and software package at a sampling frequency of 1000Hz. The data wer e time synced to the kinematic and kinetic data using an electric pulse signal whose timing was detected in a post processing step using custom designed MATLAB programs. The EMG data were gain corrected, 4 Copyright Motion Lab Systems, Inc, Baton Rouge, LA USA 5 MathWorks Inc, Massachusetts, USA
128 demeaned, filtered using a fourth order Butterworth band pass filter (f c =10 200Hz), rectified and smoothed using a fourth order low pass filter (f c =10 Hz). Data quality was visually inspected using a custom designed MATLAB program to before they were extracted for further analysis. These quality checks all owed the user to exclude unusable steps where the subject did not place their entire foot on the force plate, or the EMG signal was saturated. 5.2.3. Outcome M easures Ground reaction forces. Variables were defined from the anterior posterior ground reactio n forces (A P GRF) and were defined as follows: 1) propulsive impulse is the time integral of the positive A P GRF, 2) braking impulse is the time integral of the negative A P GRF. Propulsive and braking impulses were calculated within each bin of the stan ce phase. The percentage of total propulsion generated by the paretic leg was calculated by dividing the propulsive impulse of the paretic leg by the sum of the paretic and non paretic propulsive impulses and was referred to as Paretic propulsion (PP). PP is a quantitative measure of the contribution of the paretic leg in propelling the center of mass forward during walking 46 We also extracted the loading and u nloading magnitude peak and loading and unloading magnitude rate. Loading and unloading peaks were the maximum vertical GRF observed during the first and the second double limb support phase respectively whereas the rates were calculated as the slope of th e vertical GRF curve from heel strike to loading peak and unloading peak to toe off respectively. Electromyography. Percentage integrated EMG was calculated for each bin for each of the eight muscles. It is calculated as the area of EMG for each gait cycl e bin normalized to the area of the EMG for total gait cycle.
129 Bin analysis. The gait cycle was separated into six bins in order to analyze muscle activity or impulse generation or power produced at various time points in the gait cycle: 1) first double li mb support after (paretic/non paretic) foot strike, 2) the first 50% (of paretic/non paretic) single limb stance, 3) the second 50% of (paretic/non paretic) single limb stance, 4) second double limb support prior to (paretic/non paretic) swing, 5) the firs t 50% of (paretic/non paretic) swing, and 6) the second 50% of (paretic/non paretic) swing. 5.3. R esults 5.3.1. Baseline Difference between the Responders and the Non Responders 126.96.36.199. EMG Responders have significantly higher percentage of integrated E MG activity for MG in Bin 3 and SOL in Bin 2 for the non paretic leg. Also, responders have higher percentage activity of SOL in Bin 5 and Bin 6 for the paretic side whereas non responders were closer to normal with low level of activity of SOL in Bin 5 an d 6. RF activity was significantly different between responder and non responder for the non paretic leg with greater percentage in Bin1 and smaller percentage in Bin 5 for non responder. Moreover, greater VL activity was observed for the non paretic leg o f the responders in Bin 2 and greater BF activity was observed for the non paretic leg of non responder in Bin1. SM showed difference in their percentage activity in Bin 5 and Bin 6 with a greater paretic limb SM activity for responders in Bin5 and Bin6 an d greater non paretic limb SM activity in Bin6. GM showed difference in Bin1 with a greater percentage of activity for non responder for the non paretic side. Please refer Table 5 2 for further details.
130 188.8.131.52. Ground r eaction forces: Responders and non responders were not significantly different for any of the GRF outcome measure s No differences at baseline were observed for the positive or the negative impulses in each of the four Bins of the stance phase as well as for the contribution of the paretic leg towards the forward progression i.e. par etic propulsion (PP). Although, not statistically significant the peak loading magnitude for the non paretic leg for the responder s was greater than the non responder (responder = 91.73 8.79, non responder s = 79.68 18.17 %BW, p= 0.06 ) at baseline. Please refer to T able 5 1 for details. 5.3.2. Changes from Pre Intervention to Post Intervention 184.108.40.206. EMG There is no significant redistribution of EMG activity for the non responders (Figure 5 1) whereas there are some significantly changes in the percentage of muscle activity for responders in the various bins as shown in Figure 5 2. 220.127.116.11. Ground r eaction forces: Responders improved their PP post intervention (pre=0.23 0.17 vs. post intervention=0.27 0.18, p=0.028), whereas non responders although not significantly decreased their PP from 0.2 0.15 to 0.13 0.15. Responders also improved their positive impulses for both paretic and non paretic leg for Bin 3 and Bin 4 and increased their negative impu lses for Bin 2 on both sides and for Bin 1 for the Non paretic side. In addition, responders also decreased their negative impulses in Bin 4 on both side. On the other hand, non responders improved their positive impulses in Bin 3 and negative impulses in Bin 2 for the non paretic side. Please refer to T able 5 1 for details.
131 In addition, responders improved their loading and unloading magnitude peak for the paretic side and the loading and unloading magnitude rate for both the paretic and the non paretic s ide. On the other hand, the non responders improved their loading magnitude peak and unloading magnitude rate on both sides whereas they increased the loading magnitude rate only for the paretic side. 5.4. Discussion To begin with Non responders seem to a ctivate all their muscles maximally in Bin 1 of the paretic leg and Bin 4 of the non paretic leg which correspond s to the double limb support phase when paretic leg is unloading and the non paretic leg is loading. It is possible that their strategy is to a ctivate all the muscles on the paretic side during push off and to compensate in addition by activating all the muscles on the non paretic side, although they are not able to achieve selective activation of the muscles and hence, their strategy may in fact be more detrimental than helpful. After intervention non responders do not show any change in their muscle distribution across the various bins. On the other hand, responder s show almost equal distribution of the muscle activity in all the bins across the gait cycle and sho w significant changes in the muscle distribution post intervention Responders although not different for any of the ground reaction force measure at baseline, did show changes in their ground reaction forces which may be responsible for the higher improvement seen in them for walking speed. They significantly improved their PP which is a quantitative measure for the contribution of the paretic side towards forward progression. Our findings are in accordance with the results of study by Bowden et al. who showed that their PP improved for responders while it decreased for the non responders after the locomotor training 121 Moreover, responders improved the positive impulses for both the paretic and the non paretic side
132 in Bin 3 and Bin 4 which correspond to early and late push off and negative impulses in Bin 2 which corresponds to late braking. Moreover, the responders also increased the negative impulse for the non paretic side in Bin1 or the early braking phase and reduced it for Bin 4 on both side. On the other hand, non responders seem to have achieved the modest improvement in their walking speed by show ing improvements only on their non paretic side. Overall, it can be seen that the differential response seen for improvement in walking speed between the responders and the non responders could be a result of normalization of push off braking impulses duri ng relevant phases occurring on both paretic and non paretic side for the responder improving their forward progression and hence improving the walking speed whereas the slight improvement in walking speed for the non responders was achieved through increa sed compensation on the non paretic side.
133 Table 5 1 Descriptive statistics for the ground reaction force measures for responders and non responders pre intervention and post intervention At Baseline Test RES vs. NRES at baseline Post Intervention T est Pre Post intervention RES NRES p value RES NRES RES NRES Paretic Propulsion Paretic Propulsion 0.23 0.17 0.2 0.15 0.625 0.27 0.18 0.13 0.15 0.028 0.140 Integrated impulses for each bin Positive impulse Bin1 (%BW %GC) P 4.37 3.53 5.57 7.66 0.849 5.64 6.29 3.68 3.07 0.799 0.650 NP 14.11 16.34 22.67 26.18 0.886 13.68 13.6 24.98 22.76 0.575 0.594 Positive impulse Bin2 (%BW %GC) P 2.66 3.44 1.75 3.34 0.397 1.55 3.54 0.55 1.7 0.263 0.208 NP 14.06 12.54 19 .85 17.37 0.585 14.83 22.52 21.85 17.57 0.445 0.331 Positive impulse Bin3 (%BW %GC) P 18.63 22.63 15.67 18.23 0.807 30.14 26.44 16.11 21.45 0.028 1.000 NP 39.83 29.21 61.02 37.79 0.192 78.55 48.52 72.92 43.06 0.007 0.013 Positiv e impulse Bin4 (%BW %GC) P 28.46 45.6 28.36 30.24 0.935 45.66 51.11 23.72 33.96 0.007 0.861 NP 96.48 55.28 99.02 50.21 0.796 122.37 48.98 101.49 47.43 0.009 0.925 Negative impulse Bin1 (%BW %GC) P 72.45 23.97 56.86 31.32 0.177 80.07 31.77 74.3 39.11 0.093 0.191 NP 58.55 36.19 54.48 49.5 0.508 74.1 34.41 51.9 45.6 0.013 0.470 Negative impulse Bin2 (%BW %GC) P 37.44 28.26 43.76 36.21 0.849 64.32 39.35 51.2 37.94 0.028 0.061 NP 26.78 36.87 2 3.4 33.56 0.508 52.48 52.32 24.35 36.92 0.007 0.047 Negative impulse Bin3 (%BW %GC) P 7.96 10.83 7.98 11.9 0.978 8.06 13.99 9.24 10.52 0.285 0.532 NP 4.65 7.97 0.3 0.65 0.036 2.85 4.37 0.61 1.69 0.735 0.753 Negative im pulse Bin4 (%BW %GC) P 16.81 14.85 31.38 34.63 0.461 14.71 24.08 35.16 36.64 0.007 0.233 NP 11.48 34.03 1.19 1.56 0.709 0.43 0.53 0.65 0.81 0.028 0.311
134 Table 5 1 Continued At Baseline Test RES vs. NRES at baseline Post Intervention Test Pre Post intervention RES NRES p value RES NRES RES NRES Loading and Unloading during DLS phases Loading magnitude peak (% BW) P 77.89 13.82 71.96 13.66 0.531 89.57 19.43 80.8 14.5 0.047 0.048 NP 91.73 8.79 79.68 18.1 7 0.060 94.66 11.81 89.87 13 0.678 0.044 Loading magnitude rate (% BW/sec) P 231.32 113.08 274.91 150.69 0.311 398.46 228.41 312.18 132.18 0.059 0.030 NP 255.59 91.47 220.29 237.38 0.182 389.18 193.94 255.63 209.47 0.021 0.179 Unloa ding magnitude peak (% BW) P 83.29 12.56 79.79 12.28 0.605 92.54 19.89 83.17 13.1 0.028 0.331 NP 98.43 12.17 91.32 16.03 0.310 99.85 11.67 96.96 13.08 0.374 0.179 Unloading magnitude rate (% BW/ sec) P 250.69 116.26 196.82 159.75 0 .216 382.94 197.06 249.22 169.18 0.005 0.019 NP 309.11 133.33 338.47 160.71 0.683 499.49 165.94 385.36 152.96 0.008 0.003
135 Table 5 2 Descriptive statistics for perce ntage integrated EMG in each bin for RES and NRES at pre interventio n and post intervention At Baseline Test RES vs. NRES at baseline Post Intervention Test Pre Post intervention RES NRES p value RES NRES RES NRES TA Bin 1 P 17.18 4.52 14.77 7.49 0.388 17.11 6.11 12.14 4.8 0.889 0.814 NP 24.09 5. 65 31.98 16.77 0.276 19.56 10.95 28.12 16.98 0.012 0.814 Bin 2 P 7.87 3.25 6.86 4.41 0.301 12.36 5.21 10.29 4.8 0.093 0.025 NP 16.13 9.33 10.63 6.15 0.136 18.9 4.9 13.8 5.76 0.161 0.050 Bin 3 P 9.19 3.69 7.07 3.82 0.169 12. 59 3.92 10.97 5.55 0.093 0.158 NP 12.56 4.86 10.53 5.27 0.301 18.32 5.39 15.46 7.17 0.017 0.028 Bin 4 P 27.05 9.28 35.77 16.45 0.251 18.39 6.58 30.41 13.29 0.012 0.480 NP 21.1 12.87 24.15 16.22 0.803 15.28 8.45 17.35 9.7 7 0.093 0.071 Bin 5 P 20.23 7.66 20.69 10.1 1.000 19.12 5.27 21.41 12.79 0.889 0.388 NP 14.58 6.86 13.81 6.28 0.890 15.11 4.11 13.25 5.07 0.575 0.158 Bin 6 P 18.81 7.28 15.1 6.69 0.187 20.8 4.73 15.09 5.15 0.401 0.209 NP 1 1.82 4.55 9.18 4.36 0.169 13.17 3.56 12.31 6.04 0.161 0.289 MG Bin 1 P 26.8 18.65 18.75 11.22 0.136 16.12 7.67 14.32 6.71 0.208 0.209 NP 26.37 12.39 37.36 15.48 0.106 17.71 6.01 33.91 14.05 0.028 0.754 Bin 2 P 13.29 6.39 15.81 8.74 0.559 11.78 3.72 12.55 6.27 0.779 0.015 NP 22.57 6.09 20.1 11.02 0.383 20 5.42 16.19 6.63 0.612 0.182 Bin 3 P 9.29 1.85 11.73 6.56 0.637 13.15 3.15 11.67 4.8 0.012 0.239 NP 19.66 5.19 13.42 4.86 0.006 19 .33 3.9 14.9 5.64 0.612 0.158 Bin 4 P 20.4 8.75 28.75 15.75 0.419 21.75 10.89 34.77 17.34 0.575 0.347 NP 16.12 3.93 14.13 6.77 0.569 17.05 7.49 11.87 5.05 1.000 0.388 Bin 5 P 16.52 9.52 12.84 9.55 0.487 19.27 4.29 13.13 7 .66 0.208 0.209 NP 7.59 4.61 7.38 6.11 0.653 13 3.77 11.64 6.75 0.043 0.071 Bin 6 P 13.99 5.31 12.43 7.37 0.329 18.27 6.58 13.84 5.88 0.050 0.239 NP 8.01 3.44 7.83 4.72 0.610 13.26 3.31 11.79 6.68 0.018 0.015
136 Table 5 2 Con tinued At Baseline Test RES vs. NRES at baseline Post Intervention Test Pre Post intervention RES NRES p value RES NRES RES NRES SOL Bin 1 P 21.25 7.46 18.58 9.68 0.522 14.46 5.92 15.79 6.62 0.012 0.480 NP 18.14 9.26 30.97 19. 08 0.152 17.57 10.74 25.51 15.28 0.327 0.136 Bin 2 P 10.73 5.38 10.26 7.58 0.452 12.18 4.13 13.22 7.24 0.327 0.272 NP 17.88 9.43 10.96 4.66 0.037 19.12 4.29 13.66 4.95 0.327 0.480 Bin 3 P 11.61 3.06 13.74 10.51 0.718 11.62 2.66 12.54 5.44 0.889 0.937 NP 19.29 6.18 18.91 10.03 0.419 19.85 6.73 17.09 5.84 0.401 0.147 Bin 4 P 23.24 7.5 36 18.63 0.136 18.85 7.12 28.85 15.19 0.208 0.050 NP 30.03 17.09 23.87 13.38 0.388 16.6 7.63 18.61 9.24 0.025 0.050 Bin 5 P 17.19 8.29 11.27 6.12 0.043 20.72 4.1 14.44 5.45 0.263 0.209 NP 7.64 4.55 8.28 6.11 1.000 14.72 5.16 12.02 5.19 0.012 0.034 Bin 6 P 16.28 6.84 10.42 5.11 0.032 22.52 4.37 15.44 5.32 0.036 0.003 NP 7.34 5.09 7.32 5.05 1.000 12.46 3.28 13.4 6.77 0.017 0.015 RF Bin 1 P 23.05 8.94 19.44 11.79 0.637 16.34 7.68 15.02 7.27 0.050 0.209 NP 24.24 10.13 39.62 16.04 0.020 19.3 10.18 32.92 16.4 0.036 0.050 Bin 2 P 11.24 7.08 7.61 5.79 0.207 13.9 4.87 10.12 6.76 0.161 0.158 NP 15.05 6.58 13.45 7.08 0.452 19.81 4.54 15.96 4.79 0.093 0.071 Bin 3 P 10.18 5.84 6.94 5 0.152 12.53 2.86 9.87 4.91 0.161 0.050 NP 14.85 5.74 11.14 5.21 0.121 16.19 3.44 13.3 5 5.08 0.263 0.016 Bin 4 P 19.13 8.85 29.25 19.32 0.251 19.59 9.95 29 18.04 0.327 0.814 NP 17.41 6.27 15.79 6.58 0.452 17.13 9.76 12.77 5.12 0.575 0.239 Bin 5 P 16.28 6.6 15.56 9.01 0.76 18.28 5.1 17.49 6.44 0.327 0.308 NP 14.11 10.33 8.43 6.31 0.065 13.09 4.4 11.85 6.75 0.779 0.182 Bin 6 P 20.46 7.1 21.42 12.51 0.677 19.66 5.34 18.79 7.42 0.779 0.638 NP 14.59 10.49 11.8 9 0.301 14.78 5.66 13.41 5.94 0.263 0.875
137 Table 5 2 Continued A t Baseline Test RES vs. NRES at baseline Post Intervention Test Pre Post intervention RES NRES p value RES NRES RES NRES VL Bin 1 P 23.73 13.84 19.02 10.59 0.522 16.68 7.43 15.19 9.07 0.093 0.239 NP 20.18 9.13 30.21 17.21 0.207 16.99 8.67 26.82 15.55 0.050 0.638 Bin 2 P 10.48 5.92 11.09 8.1 1.000 13.35 4.57 12.18 6.42 0.208 0.875 NP 17.64 4.23 11.81 4.9 0.010 18.19 5.2 14.48 5.3 0.575 0.754 Bin 3 P 12.12 4.88 12.99 9.42 0.760 12.12 3.26 13.32 5.75 0. 889 0.937 NP 20.61 7.9 19.43 9.44 0.637 20.01 5.51 16.64 5.07 0.889 0.050 Bin 4 P 27.02 8.98 37.73 19.59 0.251 18.4 6.25 31.19 19.08 0.036 0.182 NP 25.29 7.9 21.57 10.06 0.229 16.87 6.41 17.64 8.11 0.012 0.015 Bin 5 P 15.2 4 8.26 10.39 5.63 0.152 20.04 4.35 13.47 5.38 0.050 0.136 NP 9.24 4.77 8.64 5.92 0.718 14.65 4.61 12.86 6.49 0.017 0.012 Bin 6 P 11.71 5 9.07 6.11 0.187 19.76 4.63 14.95 5.9 0.017 0.008 NP 7.34 4.56 8.62 7.54 0.978 13.6 4.64 11.86 4.42 0.025 0.084 BF Bin 1 P 25.23 9.09 22.12 11.06 0.419 16.25 7.41 17.28 8.8 0.017 0.060 NP 27.92 9.41 39.96 15.32 0.037 20.73 9.4 34.95 18.14 0.069 0.071 Bin 2 P 11.07 6.44 7.15 4.83 0.136 13.77 3.23 10.05 4.77 0.161 0.023 NP 14.72 7.45 13.05 8.72 0.598 19.73 4.43 13.85 4.36 0.069 0.158 Bin 3 P 8.93 4.55 6.06 4.98 0.095 13.17 3.35 10.29 4.7 0.012 0.002 NP 11.85 6.13 10.54 6.84 0.677 16.48 4.08 12.51 5.88 0.025 0.158 Bin 4 P 18.29 7.11 28.97 15.23 0.065 19.35 10.44 27.22 15.43 0.484 0.875 NP 18.6 6.8 14.73 5.75 0.065 15.92 8.2 14.46 5.78 0.327 0.937 Bin 5 P 15.94 4.64 15.3 8.04 0.978 18.13 6.26 17.1 6.44 0.161 0.480 NP 12.47 5.97 8.75 6.85 0.121 12.58 5.1 11 6.19 1.000 0.875 Bin 6 P 20.79 2.66 20.61 6.57 0.846 19.67 4.95 18.35 6.09 0.484 0.158 NP 14.7 6.79 13.17 9.32 0.276 14.89 5.95 13.51 5.18 0.484 0.638
138 Table 5 2 Continued At Baseline Test RES vs NRES at baseline Post Intervention Test Pre Post intervention RES NRES p value RES NRES RES NRES SM Bin 1 P 16.05 8.3 19.93 12.61 0.487 16.94 6.5 16.38 8.66 0.674 0.530 NP 25.1 9.73 32.94 19.17 0.452 19.21 6.8 27.28 15.4 0.036 0.041 Bin 2 P 8.97 2.73 10.93 6.13 0.677 13.56 3.82 11.61 3.36 0.017 0.875 NP 16.05 5.27 13.77 5.77 0.329 17.77 3.48 14.86 3.3 0.123 0.875 Bin 3 P 8.62 2.76 8.24 3.36 0.718 12.13 4.42 11.4 4.88 0.036 0.050 NP 13.03 4.23 14.58 7.45 0.978 19.25 3.54 16.92 6.74 0.012 0.060 Bin 4 P 29.56 10.01 35.01 16.63 0.357 18.22 5.86 28 15.15 0.012 0.041 NP 21.45 8.01 18.16 10.57 0.419 16.68 5.2 17.53 7.27 0.050 0.754 Bin 5 P 19.83 5.55 13.76 5.69 0.027 1 9.9 3.76 16.47 4.63 0.674 0.347 NP 13.57 4.98 12.15 9.41 0.388 13.46 2.35 12.48 3.43 0.889 0.583 Bin 6 P 17.31 4.77 12.4 4.86 0.043 19.57 4.58 16.43 4.42 0.093 0.019 NP 11.13 3.03 8.68 4.46 0.057 13.97 3.7 11.23 4.3 0.05 0 0.084 GM Bin 1 P 22.23 6.13 18.58 7.79 0.301 17.06 7.03 14 5.54 0.025 0.034 NP 26.56 10.45 36.18 11.58 0.049 18.98 7.52 35.13 13.79 0.036 0.695 Bin 2 P 13.71 6.9 13.15 8.15 0.89 13.02 3.36 13.24 7.36 0.401 0.754 NP 19.14 6.1 17.33 8.12 0.677 18.97 5.63 15.62 7.65 0.674 0.308 Bin 3 P 10.47 4.82 9.44 6.07 0.452 12.7 2.21 11.35 5.05 0.123 0.136 NP 14.46 3.47 11.88 4.92 0.108 17.12 3.87 14.11 4.65 0.068 0.019 Bin 4 P 22.38 6.44 30.19 17.19 0.487 20.65 8.97 30.96 15.89 0.161 0.937 NP 22.73 13.35 17.49 8.64 0.522 17.13 8.1 12.84 4.55 0.327 0.023 Bin 5 P 17.15 5.67 14.79 6.83 0.207 18.54 3.33 15.13 6.47 0.161 0.754 NP 9.36 3.99 9.34 5.62 0.760 13.62 3. 19 10.58 5.09 0.017 0.754 Bin 6 P 14.38 5.31 14.15 7.92 0.559 18.36 5.78 15.61 5.62 0.012 0.008 NP 8.06 3.45 8.04 4.7 0.559 14.51 4.56 11.98 5.61 0.012 0.084
139 Figure 5 1 Percentage integr ated EMG activity in different b ins over the gait cycle for paretic and non paretic side of non responders and speed matched controls both pre intervention and post intervention. Different muscles are shown in di fferent panel (A) TA, Tibialis A nterior, (B) MG, Medial Gastrocnemius, (C) SOL, Soleus, (D) RF, Rectus Femoris, (E) VL, Vastus Lateralis, (F) BF, Biceps Femoris, (G) SM, Semitendinosus, (H) GM, and Gluteus Medius. Y axis represents percentage of integr ated EMG activity in a bin and x axis represents different bins. Gray bar represents the EMG activity pre intervention while black bars represent the EMG activity post intervention. A B
140 C D E
141 F G H
142 Figure 5 2 Percentage integr ated EMG activity in different b ins over the gait cycle for paretic and non paretic side for responders and speed matched controls both pre intervention and post intervention. Different muscles are shown in di fferent panel (A) TA, Tibialis A nterior, (B) MG, Medial Gastrocnemius, (C) SOL, Soleus, (D) RF, Rectus Femoris, (E) VL, Vastus Laterali s, (F) BF, Biceps Femoris, (G) SM, Semitendinosus, and (H) GM, Gluteus Medius. Y axis represents percentage of integr ated EMG activity in a bin and x axis represents different bins. Gray bar represents the EMG activity pre intervention while black bars rep resent the EMG activity post intervention. A B
143 C D E
144 F G H
145 CHAPTER 6 KEY FACTORS PREDICTING RESPONDERS FOLLOWING INTERVENTION POST STROKE: A MULTIVARIATE ANALYSIS 6.1. Background Heterogeneity among t he stroke population has al ways created a problem for the clinicians when choosing an intervention for walking rehabilitation. This heterogeneity could result from various factors. For example severity of the motor impairments is related to the widely variable degree to which walk ing is impaired following stroke 122 Heterogeneity in turn may be responsible for the differential responses observed after int ervention in individuals with stroke. Hence, v arious attempts have been made to tackle this problem of heterogeneity by creating classification systems to create more homogenous groups based on identifying patterns of gait dysfunction or by identifying key f actors responsible for the variable response to treatment for these individuals to guide rehabilitation following stroke. Studies vary from using a single category of variables such as stride characteristics 8 or electromyographic (EMG) patterns 15 192 to using combination of variables 37 44 in most of these studies selection of the key gait parameters used for classifying the individuals was based was based either on an observation of the indi viduals function or a visual inspection of the gait parameters 8 15 37 192 Hence most of the classifications were based on subjective opinions of clinicians except in the study by Mulroy et al. where an objective cluster analysis was used to quantita tively classify individuals into homogenous groups based on selected input parameters 44 Heterogeneity may also be responsible for the differential response to treatment usually observed in individuals following stroke with some individuals responding to a
146 greater extent than t he others. Recently researchers have tried to identify the characteristics of individuals who achieve greater improvement in their walking function following treatment 120 121 Although, these studies do provide us with meaningful information regarding the responders they all look at a myriad of gait assessment parameters which may be difficult to gather by an eve ryday clinician in the brief amount of time provided to assess an individual. Hence, there is a need to develop a parsimonious set of parameters which could differentiate the responders and the non responders. In our previous chapters we have identified in dividuals who respond to responders) based on the improvement in their walking speed and in subsequent chapters we have attempted to identify the characteristics of each of these groups and understand the me chanism of improvement for the greater improvements in the responders. However, in order to study all the demographic, clinical assessment, spatiotemporal parameters, kinematics, kinetic and electromyographic data more effectively and parsimoniously we use d a multivariate analysis to determine the key gait parameters most critical to walking recovery following treatment. The long term goal of this study is to understand and improve walking recovery after stroke by identifying the characteristics of the resp onders and the non responders We had two specific obj ectives with this study. First objective is to determine the key gai t parameters which predict the r esponders a t baseline. Second objective is to identify the primary changes which were responsible for the greater improvement in the responders.
147 6 2 Research Design and Methods This study used the data previously collected for study 1, 2 and 3 collectively Please refer to C hapter s 2, 3, 4, and 5 for patient characteristics, study design, data collection data reduction and outcome measures used for this study. We included the participant demographics the clinical assessments, spatiotemporal measures, joint angles, internal joint moment, joint power, ground reaction force measures and electromyography va riables in our multivariate analysis. 6 2 .1. Data Analysis In order to identify the key factors which may be able to predict responders at baseline we ru n sure independent screening procedure on the 225 explanatory variables which were included in the an alysis. Sure independent screening (SIS) 193 method is a screening procedure developed by Fan et al. in 2007 which is used to reduce the dimensionality of a high dimensional data. Since patterns in data are hard to find in data with high dimension we apply SIS in an effort to retain only the most important variable predictive of responders at baseline SIS is based on sure screening which refers to a property where only the i mportant variables survive after variable screening with probability tending to one dramatically narrowing down the search for important variables In SIS, the number of predictors or explanatory variables (p) could be greater than the sample size (n) and t he objective is to reduce the dimensionality from a large p to a much smaller d To implement SIS, we m ay choose d to be a conservative n / log ( n ) Once we single out the important factors using SIS, we fit the envelope model to further reduce the dimensi on Envelope model is developed by Cook et al. in 2010 and is a new parsimonious version of the classical multivariate
148 regression 194 With the variables selected by sure independence screening we build a work ing model to the data Y = + X + where X is binary, X = 1 for responders and X = 0 for non responders, and Y is an eight dimensional vector containing the variables selected by sure independence screening. Note that Y can be partitioned into two parts, the material part t hat ch anges with X and the immaterial part that does not change with X. The two parts are orthogonal to each other We would like to find the material part using the envelope model. After we fit the envelope model to the reduced feature space and get the estimat es of means for both the groups we can use these estimates in the discriminant equations to classify a new observation as either a responder or a non responder. Discriminant analysis is a statistical technique which allows us to study the differences betwe en two or more groups of objects with respect to several variables simultaneously. The basic prerequisites of discriminant analysis are that two or more mutually exclusive groups exist and which are presumed to differ on several variables. These variables are either measured at the interval or ratio level 195 Discriminant analysis is similar to a linear regression analysis which attempts to express a dependent variable as a linear combination of explanatory variables except that the dependent variable in discriminant analysis i s a categorical variable (RES/NRES). Discriminant analysis can be used either for interpretation in order to study th e ways in which a group differ that is whether we can discriminate between the groups on the basis of some set of characteristics, how well do they discriminate and which characteristics are the most powerful discriminators? Discriminant analysis can also be used for classification in order to
149 derive one or more mathematical equations in order to classify future cases in the relevant group. T he characteristics used to distinguish among the groups are called In this case, once we develop the estimates from the envelope model we can classify a new case as either a responder or a non responder base d on the discriminant equation. Using these steps we should be able to find the key gait pa rameters predictive of responders at baseline and also we will get an equation to classify a new observation as a responder or a non responder. 6.3. Results Out of the 32 individuals w ho were classified as either responder or non responder, on average there were 25 individuals with no missing data. Based on SIS, we should retain n / log (n) variables. following 8 variables in order of priority Non paretic knee isometric strength (NP_ism_knee _strength ) Age, percentage integrated EMG for Vastus Lateralis muscle in Bin2 on the non paretic side (NP_VL_Bin2) Maximum non paretic hip abduction moment during stance (NP_max_Hipabdmoment) percentage integrated EMG for R ectus Femoris muscle in Bin1 for non paretic side (NP_RF_Bin1) Paretic double limb support phase I (PDLS1) perce ntage integrated EMG for Medial Gastrocnemius muscle in Bin3 for non paretic side (NP_MG_Bin3) percentage integrated EMG for semitendinosus muscle in Bin5 for paretic side (P_SM_Bin5). Hence, these 8 variables appear to be most important in predicting res ponders at baseline. Once the data was reduced to 8 dimensions, we used envelope model to fit this data and further reduce the dimension by keeping only the material part and getting rid of the
150 immaterial portion. Using Envelope method we were able to re duce the dimension of the data to 3 degree of freedom and ended up with 3 linear combinations of these 8 variables which were able to explain the variance in Y (dependent variables). Using the estimates of the mean for Y for both the responder and the non responder group and the other constituent parameters, we were able to apply these estimates to get the following equation in order to classify a new observation y. If true the y will be classified as non responder. ify a new observation y to class 1 (non responders) if ( 0.0262) (NP_ism_knee _strength ) + (0.1692) (Age) + ( 0.0433) (NP_VL_Bin2) + ( 0.0006) (NP_max_Hipabdmoment) + (0.04) (NP_RF_Bin1) + ( 0.0226) (PDLS1) + ( 0.0312) (NP_MG_Bin3) + ( 0.0518) (P_SM_Bi n5) > 5.5408 To verify the validity of the fitted model and the equation for classification generated by Fisher discrimination, the data was divided into 2 parts and the mod el was fitted for each part to get the estimates and a subsequent discriminant equ ation which was in turn used to classify the observation in the second part. Since we had complete data set for only 23 subjects, we divided the data set so that there were 11 observations in part 1 and 12 observation s in part 2. The coefficients and the threshold for the discriminant equations for both the parts a nd the full model are given in T able 6 1. We had 3 misclassification s when we fitted the data by part1 and used part 2 for prediction, while we had 1 misclassification when part 2 was fitted and part 1 was used for prediction. On average we had a misclassification rate of or 17.4 %, for this small sample size proving the validity of our analysis.
151 6.4. Discussion The results of LEAPS trial, one of the largest multisite clinical trials completed recently show improved walking function in only 52% of individuals undergoing rehabilitation in the sub acute period after stroke 22 Results of this study appear to suggest a 50% chance that an individual will benefit from an intervention following stroke equivalent to flipping a coin. Consequently, to facilitate reh abilitation following stroke it is important to understand the characteristics of individuals who respond to treatment v ersus those who do not respond. Currently, not a huge literature exists on responders and non responders and the clinician s do not have the a priori knowledge about who will benefit from a collaborative treatment when making the clinical decision Recently two studies have studied the characteristics of individual s who respond with greater changes in their walking speed following intervent ion 120 121 Bowden et al. found that only three clinical variables were different at baseline: ag e, Fugl M eyer assessment score (FMA) and the synergy subsection of the Fugl M eyer assessment which examines the ability of an individual to perform voluntary isolated movement independent from mass pattern of whole limb co activation (FMA S) with responder s older than the non responders and scoring more for FMA and less for FMA S than non responders. Mulroy et. al., on the other hand, showed no significant difference between their responder and non responders for age and a significantly higher score for FMA for responders. However, both these studies looked at only the clinical and behavioral characteristics of responders at baseline. In our previous chapters we have individually looked at the all the gait parameters including the biomechanical (joint angles moment, power and ground reaction force measures) and neuro biomechanical (EMG) characteristics of responders in addition to the clinical and behavioral measures. We
152 found th at the responders did not differ from the non responder for any of the clinical assessment; however, they differed for various biomechanical and neuro biomechanical measures Even though, our previous studies provide us with critical knowledge about the difference between the two groups it will be even more worthwhile from a clinical point of view if we are able to identify a priori individuals who have the potential to respond better after treatment. In this study we used a multivariate approach to identify the key gait parameters which are predictive of responders at baseline. We fo und that 8 variables are best able to differentiate responders: Non paretic knee isometric strength, Age, Vastus Lateralis muscle activity during fi rst half of single limb support on the non paretic side Maximum non par etic hip abduction moment when in st ance, Rectus Femoris muscle activity during Loading phase of the non paretic side, p aretic double limb support phase I when the paretic side is accepting weight while the non paretic side if pushing off Medial Gastrocnemius muscle activity during early p ush off of non paretic side semitendinosus muscle activity during first half of swing for paretic side. Our discriminant analysis provides us with classification criteria, based on these 8 measures. For any future case, we should be able to classify that individual as a potential responder based on this classification criterion.
153 Table 6 1 S hows the coefficients and threshold for the discriminant equations for full model and the model fitted on the 2 parts of the data set Variables Coefficients Full Part1 Part2 NP_ism_ knee _strength 0.026 0.043 0.017 Age 0.169 0.237 0.253 NP_VL_Bin2 0.043 0.023 0.306 NP_max H ipabdmoment 0.001 0.000 0.005 NP_RF_Bin1 0.040 0.049 0.074 P DLS1 0.023 0.035 0.404 NP_MG_Bin3 0.031 0.041 0.168 P_SM_Bin5 0.052 0.122 0.208 Threshold 5.541 4.050 0.609
154 C HAPTER 7 CONCLUSION Stroke is the leading cause of physical disability in adults worldwide. On average, someone in the United States has a stroke every 40 seconds. Only one third of the individuals out of the two third who experience walking impairment in the acute phase post stroke are able to achieve sufficient improvement to walk independently 167 Since impaired walking contributes significantly to functional disability following stroke 19 restoration of walking function is one of the most important goals of stroke rehabilitation 6 20 21 A Recently conducted multisite clinical LEAPS trial suggest improvement in walking function for only 52% of individuals in the subacute phase of stroke followi ng rehabilitation 22 Hence, there is a need to understand the characteristics and the mechanism of improvement for individual who respond to an intervention versus The long term objective of this dissertation is to facilitate rehabil itation of walking function following stroke. We aim to accomplish that by answering two questions: 1) what are the clinical, behavioral, biomechanical and neuro mechanical gait parameters which differentiate between responders and non responders at baseli ne. 2) To understand the differential mechanism of recovery for the responders and the non responders. To begin with we wanted to see whether at the level of general demographics and clinical assessment scales, information readily available at the clinica l level, we would be able to predict responders. Similar work done by Bowden et al 121 show baseline differences for age, measures of motor control (FMA and FMA synergy) between the responder and non responder while Mulroy et al 120 show difference for the
155 measure of motor control (FMA) as well but no difference between the age. Our study (Chapter 3) shows no differences at baseline for any of the clinical measure except for age. Although, the results for age were variable with responders in our study younger than non responder and vice versa for Bowden et al. study. Other biomechanical variables diff erent at baseline between the responder and non responders, primarily greater non paretic hip abduction moment during stance, greater paretic hip abduction angle during swing and higher non paretic medial gastrocnemius activity during Bin3 of the gait cycl e appear to suggest better lateral stabilization of pelvis to achieve better weight acceptance by the non paretic leg. As stabilizing the trunk mass over the hip introduces high demand for muscular control in the stance phase and the rapid transfer of body weight onto the loading limb requires active lateral stabilization of the pelvis over the hip especia lly in the loading response 187 this may be the reason responders are able to achieve higher improvements in their walking speed with treatment. After intervention bo th RES and NRES appear to show improvement in their walking speed and spatiotemporal measures, however, only RES appear to have meaningful changes in their walking function. RES appear to show both restoration and compensation both proximally and distally as shown by the improvement in both H3 and A2 power bursts on both paretic and non paretic side. RES achieved the improvement in their walking speed by improving the contribution of the paretic side during forward propulsion as represented by the paretic propulsion, and improved the positive impulses during both early and late phases of push off on both sides. Whereas the moderate improvement seen in the walking speed of the NRES could be attributed to compensation by more proximal muscles on the paretic side and by the non paretic
156 leg as shown by improvement in the H1 and H3 power burst on the paretic side as well as improvement in positive or propulsive impulse in early push off on the non paretic side, respectively. Although, from these studies we get i nformation regarding the characteristics of responders and non responders at baseline we still are not able to a priori classify an individual as responder or non responder. This may be especially beneficial in stroke rehabilitation as it will help us to i dentify individuals who have the ability to benefit from an intervention. So, our last objective with this dissertation was to use a multivariate approach to identify the key gait parameters which discriminate between responder and non responders and to fi nd a way to a priori classify a new patient. We identified 8 key variables including non paretic knee isometric strength, age, Vastus Lateralis muscle activity during first half of single limb support on the non paretic side, Maximum non paretic hip abduct ion moment when in stance, Rectus Femoris muscle activity during loading phase of the non paretic side, paretic double limb support phase I when the paretic side is accepting weight while the non paretic side if pushing off, Medial Gastrocnemius muscle ac tivity during early push off of non paretic side, Semitendinosus muscle activity during first half of swing for paretic side, such that if we had the following 8 variables by inputting there values for a particular individual in the discriminant equation w e would be able to classify him as a r esponder and the non responder.
157 APPENDIX OUTCOME MEASURE S
158 Primary Outcome Self selected walking speed (SSWS) Spatiotemporal Outcomes Cadence Number of steps per unit of time (steps/min) Stride length Linea r distance between corresponding successive points of contact of the same foot i.e., distance measured from heel strike to heel strike of the same foot. Paretic single limb stance Period of gait cycle when only the paretic foot is on the ground and non paretic leg is lifted off the ground for the swing phase. Non paretic step length Distance measured from heel strike of paretic foot to the heel strike of the non paretic foot. Paretic double limb support phase I Period when both the feet are in conta ct with the floor and the paretic foot is accepting weight. Paretic double limb support phase II Period when both the feet are in contact with the floor and the paretic foot is preparing for toe off. Joint Angles Hip angle at initial contact. Max hip flexion angle in swing. Max hip extension angle in terminal stance. Hip adduction angle at initial contact. Max hip abduction angle in swing. Max hip adduction angle in stance. Max hip external rotation angle in swing. Knee angle at init ial contact. Max knee flexion angle in loading response. Max knee hyperextension angle in loading response. Max knee flexion angle at pre swing. Max knee flexion angle in swing.
159 Max knee extension angle in mid stance. Ankle angle at initi al contact. Max ankle dorsi flexion in terminal stance Max ankle plantar flexion in terminal stance Max ankle dorsi flexion in swing Max ankle dorsi flexion in stance Max ankle rotation in swing Joint Moments Max hip flexion moment in load ing response Max hip flexion moment in terminal stance Max hip abduction moment in stance Knee extension moment at initial contact Max knee extension moment in loading response Max knee extension moment in mid stance Max knee flexion mome nt at pre swing Max ankle plantar flexion moment Joint Powers Hip Power at H1 Maximum between bin event 1 and bin event 2 Hip Power at H2 Minimum between bin event 2 and bin event 5 Hip Power at H3 Maximum between bin event 4 and bin event 6 Kne e Power at K1 Minimum between bin event 1 and bin event 2 Knee Power at K2 Maximum between bin event 2 and bin event 4 Knee Power at K3 Minimum between bin event 5 and bin event 6 Knee Power at K4 Maximum between bin event 6 and bin event 7
160 Ankle P ower at A1 First local minima between bin event 1 and bin event 4 Ankle Power at A2 Maximum between bin event 4 and bin event 5
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177 BIOGRAPHICAL SKETCH Shilpa Patil received her Bachelor in Physical Therapy from University of Indore, Madhya Pradesh, India. She worked for one year imparting ph ysical therapy to adults in an outpatient setting in Telco Hospital, Jamshedpur, India. Her strong interest in an interdisciplinary approach to rehabilitation encouraged her to pursue the Rehabilitation Science Doctoral program at University of Florida. O ver the course of her PhD she has been supported by various sources namely, Grinter Scholarship through the University of Florida, teaching assistant ship for four years of her graduate education through department of Physical T herapy, Brain Rehabilitation Research Center, VA RR&D project no B29729R and VA RR&D Research Career Scientist (F7823S, Patten) through the Department of Veterans Affair s and Research assistantship for last 2 years where she was funded from a industry partner Tibion Corporation. Her research employed biomechanical measures to understand pattern of walking in persons who have had a stroke and she was guided under the expert tutelage of Dr. Carolyn n Patten. In the near future, Shilpa plans to use her doctoral education to actively pu rsue teaching and research in neurologically impaired populations. The overall aim of her research is to understand recovery following stroke and to improve therapy in individuals with neurologic diseases.
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