This item is only available as the following downloads:
1 ASYMMETRIC LOAD CARRYING WHILE WALKING ON A TREADMILL : GAIT KINEMATICS AND LOWER LIMB COORDINATION By JUNSIG WANG A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF S CIENCE UNIVERSITY OF FLORIDA 2012
2 2012 Junsig Wang
3 To my family and friends, for all their support
4 ACKNOWLEDGMENTS I would like to thank my advisor, Dr. Mark Tillman for the opportunity to study Biomechanics under his guidance. Dr. Tillman s knowledge, guidance and wisdom have allowed me to complete this project at this time. I would also like to thank my committee members, Dr. Chris Hass and Dr. Christopher Janelle for your time and input. Thank you to Ryan Roemmich and Jaimie Roper for all of their help and input as you assisted me in Biomechanics lab throughout the past two years.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURE S ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 11 Specific Aims ................................ ................................ ................................ .......... 14 Hypotheses ................................ ................................ ................................ ............. 15 2 LITERATURE REVIEW ................................ ................................ .......................... 16 Human Locomotion and the Phases of Gait ................................ ........................... 16 Limb Coordination ................................ ................................ ................................ ... 19 Continuous Relative Phase ................................ ................................ ..................... 21 Influence of Asymmetrical Load Carrying on Gait ................................ ................... 23 3 METHODS ................................ ................................ ................................ .............. 31 Participants ................................ ................................ ................................ ............. 31 Instrumentation and Task ................................ ................................ ....................... 31 Procedures ................................ ................................ ................................ ............. 32 Data Processing ................................ ................................ ................................ ..... 33 Gait Parameters: Hypothesis 1 ................................ ................................ ......... 34 Limb Coordination: Hypothesis 2 ................................ ................................ ...... 34 Statistical Analyses ................................ ................................ ................................ 35 4 RESULTS ................................ ................................ ................................ ............... 39 Gait Parameters: Hypothesis 1 ................................ ................................ ............... 39 Limb Coordination: Hypothesis 2 ................................ ................................ ............ 40 Intralimb Coordination ................................ ................................ ...................... 40 Interlimb Coordination ................................ ................................ ...................... 41 5 DISCUSSION ................................ ................................ ................................ ......... 50 Kinematic Gait Parameters: Hypothesis 1 ................................ .............................. 50 Limb Coordination: Hypothesis 2 ................................ ................................ ............ 55 Limitation of Study ................................ ................................ ................................ .. 60
6 LIST OF REFERENCES ................................ ................................ ............................... 67 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 72
7 LIST OF TABLES Table page 4 1 Comparisons of the loading conditions for gait kinematics ................................ 42 4 2 Comparisons of RMS difference for intralimb couplings ................................ ..... 43 4 3 Comparisons of RMS difference and CCC for interlimb couplings ..................... 44
8 LIST OF FIGURES Figure page 2 1 Gait p hases and subdivisions of stance and swing phase (Kirtley, 2008) .......... 29 2 2 Stride and step: A step is defined as the interval between heel contact of opposite feet. Two steps compose one gait strid e ................................ .............. 29 2 3 Illustration of each segment angle and phase plot ................................ .............. 30 3 1 Illustration of four different load conditions ................................ ......................... 37 3 2 Bertec Instrumented Treadmill (Dual belt treadmill, Bertec, Columbs, Ohio, USA) ................................ ................................ ................................ ................... 38 3 3 Illustration of plug in gait model in lower extremity with 16 lower extremity markers ................................ ................................ ................................ .............. 38 4 1 Effect of three different loading conditions ( Figure 3 1) on stride length, cadence, and step width. *P< .05. ................................ ................................ ...... 45 4 2 Effect of three different loading conditions ( Figure 3 1) on swing/stance ratio. *P< .05. ................................ ................................ ................................ ............... 46 4 3 RMS difference in thigh shank coupling during both stance and swing phase for the loaded and unloaded sides. *P<. 05. ................................ ....................... 47 4 4 RMS difference in shank foot coupling during both stance and swing phase for the loaded and unloaded sides. *P<. 05. ................................ ....................... 48 4 5 RMS difference and Cross correlation coefficient for thigh thigh coupling over a gait cycle. *P<. 05. ................................ ................................ ........................... 49 5 1 Mean CRP curves in thigh shank on the loaded side during stance phase for baseline (no load) and each experimental condition (n=24). .............................. 62 5 2 Mean CRP curves in thigh shank on the unloaded side during stance phase for baseline (no load) and each experimental condition (n=24). ......................... 63 5 3 Mean CRP curves in shank foot on the loaded side during stance phase for baseline (no load) and each experimental condition (n=24). .............................. 64 5 4 Mean CRP curves in shank foot on the loaded side during swing phase for baseline (no load) vs condition 1 and 3 (n=24). ................................ .................. 65 5 5 Mean CRP curves in thigh thigh coupling over a gait cycle for baseline (no load) and each condition (n=24). ................................ ................................ ........ 66
9 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science ASYMMETRIC LOAD CARRYING WHILE WALKING ON A TREADMILL : GAIT KINEMATICS AND LOWER LIMB COORDINATION By Junsig Wang August 2012 Chair: Mark Tillman Major: Applied Physiology and Kinesiology Bags (backpacks and single sling/messenger bags) have become a daily necessity for individuals of all ages. C arrying single strap bags induces asymmetrical loading and could be harmful to the human body due to altered postures while walking The purpose of this study was to investigate the effect of different load carriage on gait kinematics and coordinative patterns in the low er extremities. T wenty four university students participated in this study and walked on a treadmill at their preferred pace under three different load conditions: condition 1 (5% of body weight in messenger bags on each shoulder hanging vertically), condi tion 2 (10 % of body weight in a messenger bag on one shoulder hanging vertically ) and condition 3 (10 % of body weight in a messenger bag on one shoulder with the bag draped across the trunk to opposite hip). We examined gait kinematics (stride length, cadence, step width and swing/stance ratio) and coordinative patterns in terms of intralimb and interlimb coupling utilizing Continuous Relative Phase analyses (CRP). CRP was evaluated over three interlimb (thigh thigh, shank shank, and foot foot) and four intralimb couplings (thigh shank and shank foot in both legs) T he results were analyzed by using repeated measures one
10 way Analyses of Variance (ANOVA) and indicated improved gait kinematics (step with and swi ng/stance ratio) and coordinative patterns (thigh shank, shank foot and thigh thigh couplings) during bilateral carriage compared to unilateral load carriage. Furthermore, asymmetric load carriage may have the potential to alter gait patterns and coordinat ive mechanisms in the lower extremities which may be associated with the risk of falling in taxing circumstances (e.g. slope, stairs, wet floors, etc .) Our results provide a picture of the adaptive mechanisms utilized by the locomotor system under external loading constraints
11 CHAPTER 1 INTRODUCTION People frequently carry loads using bags with shoulder straps. This allows individuals to transport a variety of items and still have their hands free. Bags (backpacks and single sling/messenger bags) have become a daily necessity for most people and are utilized by individuals of all ages. Backpacks are used by soldiers, hikers, and students. S tudents commonly use backpacks to carry their books, computers, spo rts equipment, and other items on a daily basis ( Negrini et al. 1999; Grimmer et al. 1999; Grimmer & Williams, 2000; Whittfield et al. 2001 ). In recent years, single strap bags have become more popular with students although they have been used extensively by bicycle couriers for years and even by riders of the Pony Express as early as 1860. The majority of previous research related to carry ing loads has been related to conventionally worn backpacks. In fact, carrying symmetrically loaded backpacks using both straps influences gait kinematics (Birrell & Haslam, 2009), posture and heartrate (Simpson et al. 2011a), muscle activity pattern s (Simpson et al. 2011b), balance (Pau et al. 2011; May et al. 2009), and even decision making (May et al. 2009). Wearing backpacks has also been suggested as a possible treatment for osteoporosis (Wendlova, 2011) and camptocormia ( Sakas et al. 2010). However, there is a relative dearth of research concerning single strap bags that are associated with requisite asymmetric loading. Asymmetric loading occurs when load center of mass is displaced laterally in the frontal plane ( De Vita et a l 1991) which is observed when carrying a single sling or messenger bag This displacement of load center from body mid line could affect the
12 gait pattern and cause back pain, as well as, injury of lower limbs and joints. Although carrying backp acks over both shoulders could be the best way to prevent back pain ( Macias et al. 2008; Korovessis et al. 2005) students also choose asymmetrical load carriage instead of symmetrical for a variety of reasons ranging from convenience to fashio n In other words, carrying single strap bags are not conductive to the health of ( Pascoe et al. 1997; Negrini et al. 2007; Macias et al. 2008; Matsuo et al., 2008). S tudents induce an asymmetric load by carrying their backpack with one strap on one shoulder instead of both shoulders, concentrating the load on one side of the body. This loading can place considerable stress and strain on the shoulder muscles ( Marras et al. 1997) It also seems that by carrying a single strap on one shoulder, individuals must bend their trunk contralaterally to address the demand for dynamic balance. Accordingly, increased trunk flexion toward the contralateral side ( DeVita et al. 199 1; Pascoe et al. 1997) due to asymmetric load carrying causes an increase in hip abduction torque ( DeVita et al. 1991; Matsuo et al. 2008) This indicates that asymmetric loading alters dynamic balance when wearing a backpack with one strap compared to both straps ( Pascoe et al. 1997). In addition, the increased lateral bending caused by asymmetric loading increases spinal stress ( DeVit a et al. 1991; Pascoe et al. 1997; Legg & Cruz, 2004) The alterations of Contralateral trunk flexion during walking may cause scoliosis or other permanent physical problems (Roaf, 1960; Hawes As a result, increased bending st ress on the trunk and spine may exacerbate any abnormalities in the biomechanics of locomotion. These alterations suggest that single strap bags may be a contributor to abnormal posture and motion of
13 the lower extremities in gait Interestingly, the loads and mechanical adaptations experienced when carrying loads tend to take place in the frontal plane. However, the goal of load carriage during gait is to transport various items in a forward (sagittal plane) direction. Therefore, most of the parameters examined in the current study were sagittal plane variables. In addition, sagittal plane movements of the lower extremities are typically the most meaningful measures compared to the other two planes in terms of moving the body forward. Physiological res ponses of single strap bags on gait measures can be seen carrying golf bags. The muscle activation to maintain upright position when carrying the single strap of a golf bag on one shoulder, compared to double strap bags, may cause higher demand on metaboli c cost that induces fatigue ( Ikeda et al. 2008) Asymmetric load carriage is associated with higher oxygen uptake ( Ikeda et al. 2008; Legg et al. 1992) and heart rate ( Ikeda et al. 2008) than backpack load carriage and could increase muscle activation ( Neumann et al. 1996) and fatigue. F atigue caused by single strap athletic bags could be one factor that may change posture and gait pattern. In attempts to study posture and gai t, previous researchers have modeled lower extremity movement as a pendulum, with the segments of the leg oscillating during the gait cycle. Coordinative structures have been useful tools to resolve and map each segment pattern during gait. In movement sci ence, examining how two oscillators are coupled together during a limit cycle has been an important concern since human movement involves coupling of multiple degrees of freedom in the human body. Moreover, previous researchers have attempted to quantify c oordinative patterns of two oscillating segments during gait cycles by utilizing several methods in terms of
14 dynamical system theory (e.g. continuous relative phase, vector coding, and cross correlations). In this study, we use d continuous relative phase t o quantify and analyze limb coordination of the lower extremities during the gait cycle. More specifically, we adopt ed CRP to investigate effect of carrying messenger bag that affect inter limb and intra limb coordination during the gait. In sum, t here ha s been a noticeable increase in single strap bags sales which would indicate that more people are carrying them (Vicky, 2001). With the research on numerous type of bags (schoolbags, military bags, athletic bags, and messenger bags) showing that indeed, ba gs have a direct effect on the movement of the human body, there seems to be a lack of research on other types of bags such as single strap bags. In everyday life, bags can be considered necessities and therefore must be considered if the movement is to be fully understood. A few researchers have investigated how asymmetric load carrying affects the biomechanics of human movement. However, few data exist regarding asymmetric load carriage and gait kinematics in terms of coordination patterns of the lower ex tremities. Therefore, we attempt ed to show evidence indicating that carrying single strap bags induces abnormal coordination patterns in the lower body while walking. Specific Aims The aims of the research were 1) to investigate gait kinematics in response to three different loading conditions and 2) to evaluate lower extremity limb coordination in response to different loading conditions in university students during treadmill walking at a self selected pace Ba seline condition s w ere not include d for gait kinematics because t he author focus was to measure gait alteration s in response to bilateral and unilateral load carriage
15 Hypotheses The following general hypothes e s and specific sub hypotheses were tested. 1. Gait pattern would be altered when carrying two messenger bags (one on each shoulder) compared to a messenger bag on one shoulder A. Stride length would de crease and cadence w ould increase during symmetric loading compared to asymmetrical loading. B. Step width would decrease during symmetric loading compared to asymmetric loading C. Swing/stance ratio would decrease on the loaded side and in crease during symmetric loading compared to asymmetric loading 2. Lower limb coordination (inter and intra limb coordination) w ould be altered when carrying two messenger bags (one on each shoulder) compared to a messenger bag on one shoulder A. RMS difference s for intralimb (thigh shank and shank foot couplings ) and interlimb (thigh thigh, shank shank and foot foot coupling s) would decrease during symmetric loading compared to asymmetric loading B. Cross correlation coefficient valu e s for intralimb and interlimb coupling s would increase during symmetric loading compared to asymmetric loading
16 CHAPTER 2 LITERATURE REVIEW Single strap bags have become more popular with students in recent years, but have been linked to altered gait kinematics (Pascoe et al. 1997). The proposed study will be undertaken to examine the kinematic changes that may lead to variations in the lower extremity movements and coordination. This chapter will be divided into four sections. Section one will describe human locomotion and the phases of gait. Section two will describe limb coordination during human gait. Section three will describe a Finally, section four will describe the influence that asymmetri cal load carrying has on human locomotion as well as coordination patterns of lower extremity. Human Locomotion and the Phases of Gait Human gait is very complicated, involving continuous coordinated bipedal locomotion. As a person moves forward, one of the lower limbs serves as a mobile source of support while the other limb moves forward to become the new support site in front of the current support site. To transfer body weight from one limb to the other, both are alternately placed on the ground. Thi each gait cycle begins with ground contact of the heel and ends with the following heel co ntact of the same limb (Figure 2 1 ). Several approaches have been proposed to fully investigate the human gait cycle and numerous terminologies to define specific human walking events have been introduced. In this chapter, we will look over the descriptive phrasal terminology yielded from previous observational and kinematic analyses of normal gait (Perry 1992; Sutherla nd et al. 1994).
17 Since this cycle of events is repeated by each limb with reciprocal motion timing to the following part, there is no specific ending or starting point. However, for gait analysis, an initial point of gait will be used to define the beginning of each gait c ycle. Each gait cycle is divided into two periods (stance and swing) based on heel contact points of reciprocal foot motion (Figure 2 1 ). The swing phase is the time period in which the foot is not in contact with the ground, starting with the point of toe off and ending with the point of heel contact. The stance phase of the gait cycle is the time period in which the foot is in contact with the ground. The stance phase begins with heel contact, and ends with the point of toe off. The stance and swing phases are subdivided into three different intervals based on the sequence of heel contact. The stance phase is subdivided into three smaller phases: initial double support, single support, and terminal double support. The gait cycle b egins with initial double support phase when both feet are on the ground after initial contact. When the opposite foot is lifted and starts to swing, single support begins. In this phase, one leg is in contact with the ground to support the entire body w eight, while the other leg swings forward. When the swing leg begins a new heel contact, the single support phase ends and terminal double support phase begins. Terminal double support continues until the original stance limb is lifted to make a new swing phase. The swing phase is also subdivided into t hree phases: initial swing, mid swing, and terminal swing. The initial swing phase is the time from when the swing foot leaves the ground to when it crosses the stance foot. In this phase, the foot is off th e ground and accelerating forward. Next, the mid swing phase begins when the swing limb is opposite the stance foot and ends when the tibia is vertical. In the mid swing
18 phase, the swing foot moves forward and overtakes the limb in stance. Terminal swing i s from the time when the tibia is vertical until the foot makes contact with the ground. Finally, the decelerating swing limb completes swing phase in preparation for the stance phase. In normal gait, the stance phase accounts for approximately 60% and the swing phase occupies around 40% of the total gait cycle although the precise duration of the time of the stance and swing phases of the gait cycle are inversely re lated to the walking velocity in that both the stance and swing phases decrease in duration as velocity increases (Mann, 1982). Likewise, when walking velocity slows, the times of the stance and swing phases become longer. Over the past several decades, n umerous temporal technical terms describing gait have been produced to help us scrutinize human gait. Moreover, a variety of gait parameters has been codified to analyze and quantify gait. The terminology related to human walking began with descriptive phr ases obtained as a result of observational and kinematic analysis of normal participants (Perry, 1992). For example, stride is the time period from the heel strike of one foot to the following heel strike of the same foot. Steps, regarded as the ti ming between two limbs, are indicated by the time period of initial contacts of both feet. That is, a step is the time period from the heel strike of one foot to the heel strike of the other foot. Two steps have been identified in one gait stride, since th e other initial contact begins at the midpoint of one stride (Perry, 1992 Figure 2 2 ). The evaluation of walking is the primary tool for describing human gait patterns. In the field of biomechanics, gait analysis is a method by which modern technologies are
19 used to incorporate information from a number of inputs to illustrate and analyze the dynamics of gait (Perry, 1992). This basic approach to evaluating gait will be the focus of the current research. It will provide evidence which will be used to address the specific aim. Limb Coordination As previously stated, human gait is a complicate d movement that includes cycles and coordination of each segment. In bipedal locomotion, limb coordination is crucially important and must be altered according to demands of varying external circumstances (Reisman et al. 2005). To adapt to the demands of various environments, specific coordinative patterns occur both within limb segments and between limbs. For example, coordination of oscillating segments may change based on external restraints, such as surface propertie s, or internal restraints, such as a neurological disease (Haddad et al. 2005). Functional gait demands flexible limb movements to accommodate for different external constraints (Reisman et al. 2005). Inter segmental coordination demands compli cated interaction between the motor output of the neuromuscular system, biomechanical factors, environmental factors, and task constraints (Higgins, 1985; Kugler & Turvey, 1987). I n response to the demands of a specific task, muscles must be used in c ombination to bring about particular movements in several joints (Turvey, 1990). Therefore, movement coordination may involve both muscular action and interactions at each joint. This approach to human movement may allow scientists to implement important i nsight in their investigation of the neurological system. Thus, to generate complex movement incorporating several segments or joints ( Forner Cordero et al. 2005). C oordinative inter joint and inter segmental movements are a
20 strategy of the central nervous system to control movement and maintain stability during human locomotion (Kurz et al. 2004) Different coordination patterns have been observed for various neurological disorders (i.e. hemiparesis, parkinson's disease, stroke). In hemiparetic gait, an overactivated rectus femoris during swing phase was associated with changing thigh shank coordina tion ( Forner Cordero et al. 2005). Other be involved in freezing of gait (Plotnik et al. 2005). Therefore, coordinative inter segmental movement results from ind ividual muscles and neuropathways (Stergiou 2004). Effective organization and modeling of gait coordination has been an important focus for many researchers. Traditionally, biomechanical tools have been utilized to analyze human movement patterns. However, scientists need novel approaches to gain a more advanced understanding of the organization of human movement. The two components of this approach are the multifactorial and nonlinear relationships of the gait pattern (Stergiou 2004). More over, mapping coordination patterns in limbs during gait provides a clear mechanism of the neuromuscular system in low dimensional terms (Kurz et al. 2004). In a biomechanical system, to organize a coordinative model, researchers have reduced the hig h available degrees of freedom in segmental movement (Hamill et al. 1999). The concept of coordinative structure comes from and made efforts to simplify the many degrees o f freedom in segmental movements and reduce independent variables requiring control (Bernstein 1967 ; Turvey, 1990). In conclusion, previous researchers studying gait coordination have been focused on organizing the system for functional movement pattern, reducing numerous independent
21 variables and, summarizing the relationship between various components during gait. Examining limb coordination patterns under external constraints (i.e. asymmetric load) during gait may provide insight into specific control m echanisms and human movement adaptations under various environmental conditions. Continuous Relative Phase Researchers have used different nonlinear dynamic techniques to investigate variability in human movement based on the dynamical systems theory (Miller et al. 2010). One prevalent dynamic systems analysis for studying coordination of segmental movement can be evaluated through continuous relative phase (CRP). This measure has been used to quantify the coordination between different body se gments in several activities (Varlet & Richardson, 2011) This approach to investigating the coordinative pattern of gait is to recreate it as a dynamic system and study its stabilizing features. Moreover, C RP indicates the aspects of interacting segments during the entire movement cycle. Therefore, t he relative phases of several oscillating segments can be measured to quantify segmental coordination and evaluate movement patterns. Prior to calculation for C RP, each segment angle (Figure 2 3) is normalized for each trial using the following equation: Also, angular velocity is normalized the following equation:
22 This is done by plotting the posing of a segment angle versus the angular velocity of et al. 1999). The phase angles ( are obtained by calculating four quadrant arctangent of the ratio of angular velocity by angular position: Then the continuous relative phase is calculated by subtracting the phase angle of the proximal segment from that of the distal segment for a specific point during the gait cycle. Where continuous relative is the relative phase angle between the distal and proximal The main strength of the CRP measure is that it compresses four variables and angular velocities). When the C RP is near 0 the respective segments are in phase, while 180 of the CRP indicates that both segments are anti phase (Haken et al. ,1985 ; Kelso et al. 1986; Scholz & Kelso, 1989; Diedrich & Warren, 1995). Positive relative values indicate that the distal segment is ahead of the proximal segment, and negative
23 values indicate that the proximal segment is ahead in phase space (Clark & Phillips, 1993; Barela et al. 2000). The slope of the relative phase curve configuration indicates which segment is moving faster during the period of the gait cycle (Barela et al. 2000). A positive slope indicates that distal segment is moving faster in phase space, while a negative slope indicates that the proximal segment is move faster in phase space. Comparing the phase angles of two segments using relative phase provides insight of normal and pathological gait patterns (Kurz et al. 2004). Influence of Asymmetrical Load Carrying on Gait Because bag conditions are the main external constraints for students during gait, the choice of bags can be a crucial factor in alterations of gait patterns. It seems that by carrying sing le strap bags, abnormal gait patterns may be produced that have the potential for inducing injuries in the lower extremity. Much of the research available in the biomechanics field on asymmetrical gait has shown a detrimental influence on the human body. S pecifically, physical stress associated with carrying bags on one shoulder altered the posture and gait pattern of children (Pascoe et al. 1997). Pascoe and colleagues studied sixty one youths, without bag, carrying a one strap book bag, a two strap bag, and a one strap athletic bag. In this study, the impact of carrying book bags on static posture and gait kinematics was examined. This study utilized a two phase approach. In phase one, sixty one students who transport their school materials had a sur vey that provided descriptive and anthropometric characteristics, book bag weight, typical bag carriage, and associated physical symptoms. In phase two, ten participants were chosen for kinematic analysis based on the survey and underwent dynamic walking at a self determined pace. A 7.7kg (17% of body weight) book bag weight was used in this study. A video analysis system was employed for digitizing the movements
24 for kine matic analysis. The results of the study indicated that the load of the book bags resulted in a decrease in stride length and an increase in stride frequency and greater angular motion of the head and the trunk was observed with the athletic bag trial. Mor eover, they showed carrying bags on one shoulder caused different movement strategies such as lateral spinal bending and shoulder elevation while walking They also suggested that carrying backpacks promoted a significant forward lean of the head and trunk compared to normal walking or one strap athletic bags. In sum, they showed clear evidence that carrying backpacks or messenger bags altered the posture and gait of youths. However they did not evaluate the gait patterns of lower extremities related to the se abnormal postures. Another study focusing on the effects of carrying an asymmetric sidepack on the frontal plane joint moments in both lower extremities and in the L5/S1 joint during walking was performed by Devita and Colleagues (1991). Five healthy m ales were recruited for this study and required to walk under three load conditions: no load, a load equivalent to 10% of the subject's body weight, and a load equivalent to 20% of the subject's body weight. The participants were instructed to carr y the pack on the left experiment was designed to obtain three dimensional ground reaction force data and frontal and sagittal plane film records for deriving lower extr emity joint moments in both plane and frontal plane L5/S1 moments. The results of this study showed that asymmetric loads produced unbalanced frontal plane moments, large changes in right limb moments and smaller changes in left limb moments and caused L5/ S1 moment dominance to shift to the right side during left and right single support phase. The
25 authors conclude that since the asymmetric load caused unilateral and unbalanced use of trunk muscles on the non loaded body side for both stance phases, asymmet ric load carrying can be a greater risk factor for injury than symmetric carrying (Devita et al. 1991). Although they also showed different movement patterns such as unbalanced hip and knee joint moments that may alter limb coordination, they did not report coordination patterns in the lower body during asymmetric load carrying. A separate study provided clear evidence that carrying single strap mailbags alter the kinematics of the spine and induce stature loss (Fowler et al. 2006). They used a specific mail bag (17.5% body weight load) to simulate the task of the postal worker and attempt to quantify the effect of asymmetric load carriage on spinal kinematics and stature loss. Thirteen markers were attached on the participan and one marker over each shoe. The changes in stature measure were assessed with a stadiometer. The results of this study indicated increased forward leaning and bending of the spine while carrying the messenger bag during walking. More specifical ly, they showed up to five degrees of forward flexion in the thoracic spine in the sagittal plane and up to a 12 increase in the lumbar region in the frontal plane. Stature loss was evident in the loaded condition, producing a spinal shrinkage greater tha n the unloaded condition (12.1 1.2 mm loaded, 5.75 1.1mm unloaded). These findings provided strong evidence that carrying asymmetric loads induces abnormal postures related to spinal configuration during gait. In addition, Hadded and colleagues (2005) per formed a study on the coordinative pattern in lower extremity to asymmetrical loading during walking. In this study twelve healthy individuals were recruited to walk on a treadmill at their preferred walking speed.
26 Four different unilateral loads (0.9, 1.8 2.7, 3.6, 4.5kg) for each lower leg were worn 2.5cm above the lateral malleolus utilizing a custom made leg loading device. The researchers hypothesized that this adaptation would alter interlimb coordination while intralimb coordination would remain inv ariant. Continuous relative phase (CRP) was employed to evaluate changes in limb coordination patterns. Changes in coordinative patterns were quantified using both cross correlation and root mean square (RMS) difference measures. The result of this study i ndicated that increases in leg loads resulted in RMS changes in the interlimb level of the loaded leg. At the interlimb level, significant differences were found in both cross correlation and RMS measures (Haddad et al. 2004). The authors of this stu dy indicated that various adaptations in lower limb coordination appear at both the intralimb and interlimb levels in response to unilateral load changes. They suggested changes at the intralimb coordination level were greater than the changes in interlimb coordination, in both RMS and cross correlation measures. More specifically, at the intralimb level (the thigh shank and shank foot couplings), the RMS difference in the loaded leg increased significantly (indicating out of phase movement) during both sta nce and swing phases. At the interlimb level, the RMS differences significantly increased in all three interlimb couplings (thigh thigh, shank s hank, and foot foot). Also, the cross correlation coefficient systematically decreased with greater loads. Howev er they used a custom made leg loading device that was placed 2.5cm above the lateral malleolus. This load condition at the lower leg may cause limited leg movement due to load itself and is difficult to apply to real life. In the current study, single str ap bags carried on one shoulder were used for enhancing potential asymmetries instead of this leg load.
27 Yet another study investigated balance during asymmetric load carrying and how asymmetric loading affects lower limb coordination while walking. Five young women and six elderly women walked under three different conditions: without a bag, with a 3kg hand held bag, and with an 8kg hand held bag. The researchers also used CRP measures to analyze lower limb coordination and CRP means for each load condition were used to calculate the cross correlation coefficients. The results of this study showed that the me an of cross correlation coefficients for both interlimb and intralimb level were close to 1.0 and each participant showed the same coordination pattern. The author concluded that limb coordination is maintained under external constraints such as asymmetric loads, thus hand held load carrying minimally affected the coordinative patterns in lower limbs (Matsuo et al. 200 8 handbags as its load conditions but we us ed messenger bags to evaluate lower leg movement in re sponse to the diverse load conditions that are usually encountered by university students. Several studies have shown that asymmetrical load carrying creates issues with kinematics and coordinative patterns in lower extremity. Even though previous researc h examined gait kinematic changes and coordinative patterns in lower extremity under various loads conditions, little research has been done to show exactly how carrying a single strap bag, compared to carrying a backpack, affects gait kinematics and lower limb coordination for university students. Therefore it is important that more research be conducted to investigate the effect of single strap bag carrying on coordination patterns in lower extremity, providing insight into circumstances with a potential for injury. The present study will be an attempt to simulate real life loading conditions utilizing different
28 types of bags. Furthermore, the evaluation of coordination patterns may reveal insight regarding neuromuscular mechanisms related to gait.
29 F igure 2 1. Gait p hases and subdivisions of stance and swing phase (Kirtley, 2008) Figure 2 2 Stride and step: A step is defined as the interval between heel contact of opposite feet. Two steps compose one gait stride
30 ( A) ( B) Figure 2 3 Illustration of each segment angle and phase plot (A) Illustration of each segmental angle: thigh, shank, and foot angles in sagittal plane (B) Phase plot illustrating phase angle based on angular displacement versus angular
31 CHAPTER 3 METHODS Participants Twenty four healthy students with an age range of 18 to 3 0 (12 males and 12 female; age 21. 6 3. 6 years; height 170.9 8. 5 ; weight 67. 2 12.5 kg) participate d in this research. All participants were recruited from the University of Florida and surrounding community by word of mouth. All were free of any pathology that would prevent them from walking on a treadmill. Moreover, individuals were excluded if they had current back or neck pain, any joint pain, history of arm pain, or spine pain in the previous three months or if they were not healthy enough to handle the demands of the tests in this study. Prior to participating in the study, each subject read and sign ed an informed Twenty two participants were right handed and during conditions 2 and 3 preferred to carry the messenger bag on the right shoulder, while the other two left handed individuals p referred to carry the bag on left shoulder. Though both sides were loaded during document refer to the sides which are loaded or unloaded during conditions 2 and 3, respectiv ely Instrumentation and Task Two single strap bags (Figure 3 1 ) were utilized in this research to create three different load conditions : Two single strap bags on e on each shoulder and hanging down vertically (0% of body weight), two 5% body weight single strap bags with one on the right shoulder and one on the left (hanging vertically) and 10% body weight single strap bags in different positions while walking on a treadmill The total weight carried in
32 the b ags was based on existing literature as indicated in the following sentences Previous studies using various loads (10 20%) have shown the diverse effect on the human body during gait (Devita et al. 1991; Fowler et al. 2005; Korovessis et al 2005; Zultowski et al 2008). In fact, t he bag load for college age students has been recommended to not exceed 10 15% of the et al. 2010). Thus, t he load for the current study was determined based on these data and gu idelines Fu r thermore, t he messenger bags were positioned approximately 10 cm below the A S IS makers across the conditions. A Vicon motion analysis system with 7 high resolution cameras (Vicon Nexus, Oxford, UK) was used to collect three dimensional kinematic data during each testing condition. The cameras were positioned to record movement in the three cardinal planes (frontal, sagittal, and transverse) during the gait cycle. Kinematic data were captured at 120Hz. Calipers were used to record participants anthropometric measures and joint center locations were calculated from the static trial. All participants walk ed on an instrumented treadmill (Figure 3 2 ) for e ach load condition. The treadmill was built on two forceplates that allow ed for measuring continuous ground force data during gait. These data were use d for identifying gait events (toe off and heel strike). Procedures After meeting the qualif ications for participation, the body weights of participants were measured to determine appropriate 10% body weight loads to be carried in the different bag conditions. Participants were then prepared for retro reflective marker placement by changing into tight fitting shorts and shirts. Sixteen retro reflective
33 markers were placed on the lower extremity over bony landmarks according to the Vicon Plug in Gait marker system (Figure 3 3 ). Al l participants were instructed to walk at a self selected speed on the instrumented treadmill. To determine the "self selected speed" of each subject, the belt speed was initiated at 0. 5 m/s. The speed was gradually increased in increments of 0.1m/ s until the participant signal ed that his or her preferred speed has been reached. Participants were captured digitally as they walk ed under different loading conditions. More specifically, participants un der went testing in four different load conditions: no bag, carrying two messenger bags on both shoulders with a 10%BW load, carrying the messenger bag on one shoulder hanging vertically down to the hip with a 10%BW load, and carrying the messenger bag on o ne shoulder draped across the trunk to opposite hip with a 10%BW load ( F igure 3 1) In condition 2 and 3, t he messenger bag s were worn on the side of the preferred shoulder. They initially were asked to walk on a treadmill at their preferred pace for five minute s in each condition, with the bag order randomly assigned (by using a randomizing table). Thus, a total of four trials were completed ( 20 minutes of treadmill walking). Each participant was allowed to rest as much as necessary between trials. We coll ect ed data for the last one minute of each condition b ecause of the large magnitude of data necessary for processing. Thus, around 50 strides in each condition were recorded. Data Processing As alluded to previously, three dimensional lower extremity gait analysis was performed on all participants Kinematic data were processed and exported using the Vicon nexus 1.7.1 software program (Vicon Nexus, Oxford, UK). Marker trajectories were filtered using a fourth order Butterworth filter, with a 10Hz cutoff frequency. Then,
34 kinetic data were used to identify the stance and swing phases of the gait cycle based on each gait event (foot strike and toe off). Accordingly, the gait cycle was divi ded into two phases: stance and swing. Gait P arameters: Hypothesis 1 We examined gait kinematics (stride length, cadence, step width and swing/stance ratio) while walking on a treadmill. Stride length was defined as the displacement of the ankle marker along the walking axis during the time period from the heel strike to toe off in the same foot ( Reisman et al. 2005 ) Cadence was defined as the number of steps during one minute. Step width was de fined as the mediolateral distance from the s wing limb heel marker to the stance limb heel marker at each heel strike Swing/stance ratio was defined as the ratio between swing and stance time over a gait cycle. Around 50 gait cycles were evaluated for the gait kinematics using a custom Matlab code Limb C oordination: Hypothesis 2 Three segmental angles (thigh, shank, and foot), as well as, angular velocities were assessed from raw kinematic data exported from the Vicon system (Figure 3 3 ). Continuous relative phase (CRP) analyses were performed using Matlab. We focus ed the kinematic analysis on CRP measures during the stance and swing phases of the gait cycle, as well as, the gait cycle as a whole. S egmental angular velocities were calculat ed from segmental angles in the sagittal plane utilizing the central difference method. These data were then used to calculate phase angles from a phase plot, using the arctangent of angular velocity / angular displacement at each data point. For the intr alimb couplings, CRP was calculated by subtracting the phase angle of the proximal segment from that of the distal segment for each data point More specifically, the intralimb couplings were the thigh shank and shank foot in both limbs. For the
35 inter limb coupling CRP was calculated by taking the difference between the phase angles of both segments for each data point. The interlimb couplings were the thigh thigh, shank shank and foot foot. These procedures were described in more detail in Chapte r 2. Thus, CRP was evaluated over three interlimb (thigh thigh, shank shank, and foot foot) and four intralimb couplings (thigh shank and shank foot in both legs) during the gait cycle, as well as the swing and stance phases of the gait cycle. Since each trial had a different length cycle, the data were processed using a linear length normalization that allows the different trials to have equal data lengths for each gait cycle. In interlimb coupling, the time se ries of one limb was time shifted to match left and right foot strikes. Coordination patterns were quantified utilizing cross correlation coefficient (CCC) and root mean square (RMS) techniques. CCC was assessed by comparing the average CRP in each lo ad condition to the average CRP in the no bag baseline condition during gait cycle for interlimb and intralimb couplings. RMS difference was also evaluated by comparing the average CRP in each load condition to the average CRP in the no bag baseline condit ion. While the CCC measure indicates changes in the spatio temporal evolution of CRP patterns, RMS measures show information about the magnitude differences in relative phase between the patterns (Haddad et al. 2004). Statistical Analyses Statistical analyses were performed using the SPSS statistic s (version 20 ; SPSS Inc. Chicago, IL, USA). The effect of the different loading conditions on gait kinematics (stride length, cadence, step width, and swing/stance ratio) and limb coordination parameters were analyzed by using repeated measures one way Analyses of Variance (ANOVA). In addition, the influence of loading was further investigated for swing/stance
36 ratio and intralimb coupling by performing the statistical tests on the loaded and unloaded limbs separately. was used when appropriate. The level of statistical significance for all tests was set at P<0.05.
37 Figure 3 1. Illustration of four different load conditions B aseline (no load with one messenger bag on each shoulder hanging vertically down to the hip), condition 1 (5% of body weight in messenger bags on each shoulder hanging vertically), condition 2 (10 % of body weight messenger bag on one shoulder hanging vertically) and condition 3 (10 % of body weight messenger bag on one shoulder with the bag draped across the trunk to opposite hip).
38 Figure 3 2 Bertec Instrumented Treadmill (Dual belt treadmill, Bertec, Columbs, Ohio, USA) Figure 3 3 Illustration of plug in gait model in lower extremity with 16 lower extremity markers
39 CHAPTER 4 RESULTS Gait P arameters: Hypothesis 1 Initially, we evaluated the effect of different loading conditions on gait kinematics via stride length, cadence, step width and stance/swing ratio. A main effect for stride length was detected (F (2, 46) = 5.418, P = .008). Follow up testing revealed that stride length during condition 2 was shorter than condition 3 (p =.006 Figure 4 1 ). No other significant difference s between condition s were observed ( P >. 05 ). Also, cadence varied across conditions (F (2, 46) = 5.902, P = .005). More specifically, c adence during c ondition 2 was significantl y increased compared to condition 3 ( P = .005; Figure 4 1 ). No difference in cadence was observed in condition 1 versus 2 or condition 1 compared to 3 ( P >.05) A step width main effect was observed ( F (2, 46) = 14.481, P < .001 ) Post hoc analysis revealed that the step widths for condition 1 compared to conditions 2 and 3 were significantly decreased ( P = .002, P < .001; Figure 4 1) There was no other significant difference between conditions for step width ( P >. 05 ). Finally, t he swin g/stance ratio was assessed in both the loaded and unloaded sides over a gait cycle. As mentioned previously, though both sides were loaded during condition 1, the were loaded or unloaded during condi tions 2 and 3, respectively. A significant main effect was observed in the loaded limb ( F (2, 46) = 14.274, P < .001). In particular the swing/ stance ratio on the loaded side during condition 1 was increased compared to conditions 2 and 3 ( P < .001 and P = .001, respectively; Figure 4 2 ). N o significant difference was observed between condition 2 and 3 (P > .05). Additionally, a main effect of swing/ stance ratio on the unloaded side was noted ( F (2, 46) = 5.738, P = .006). Subsequent testin g indicated
40 that the swing/ stance ratios during condition 1 were significantly decreased compared to conditions 2 and 3 (P = .014, P = .033; Figure 4 2) N o difference was observed between condition s 2 and 3 (P >.05). A summary of these comparisons appear s in Table 4 1. Limb C oordination: Hypothesis 2 Intralimb C oordination Intralimb coupling s (thigh shank and shank foo t ) were examined for the loaded and unloaded side during the stance and swing phase to investigate the mechanism of coordinative patterns in the lower extremities over a given period. Coordinative patterns were analyzed using RMS differences an d Cross Correlation Coefficients RMS differences in intralimb coupling were evaluated over stance and swing phase s A significant main effect of RMS differences for t high shank coupling during the s tance phase in the loaded side was observed (F (2, 46) = 10.852, P < .001 ). Post hoc testing revealed that t high shank coupling during condition 1 was less than conditions 2 and 3 ( P = .01, P = .001; Figure 4 3 ). Also, on the unloaded side, a main effect of RMS in thigh shank was detected ( F (2, 46) = 5.378, P = .008). RMS changes during condition 1 were decreased compared to conditions 2 and 3 (P = .033 and P = .041, re spectively ; Figure 4 3 ) However, no significant RMS difference was observed for thigh shank coupling during swing phase (P > .05) For shank foot coupling, significant differences in RMS were observed on the loaded side during both s tance (F (2, 46) = 9. 220, P < .0 01 ) and swing phases ( F (2, 46) = 5.695, P = .0 06 ). RMS decreased during condition 1 compared to conditions 2 and 3 ( P = .02 and P = .004, respectively, Figure 4 4 ). Also, during the swing phase, the RMS difference during condition 1 in the loaded side was less than condition 3 (P = .027,
41 Figure 4 4 ). However, no significant difference s of RMS in shank foot coupling were detected for the unloaded side (P> .05) Table 4 2 illustrates the loading conditions compared to each other for RMS dif ference. Moreover, n o cross correlation coefficient effects for thigh shank and shank foot coupling for either limb were displayed. All CCC values for intralimb coupling were close to 1. Inter limb C oordination Interlimb coordination was examined via thigh thigh, shank shank and foot foot couplings. A significant main effect on RMS difference was observed in thigh thigh coupling (F (2, 46) = 5.276, P = .0 09 ) RMS difference s during condition 1 in thigh thigh coupling were significantly less than condition 2 ( P = .022 ; Figure 4 5) There were no other significant differences between conditions ( P >. 05 ). No effect on RMS changes in shank shank or foot foot was observed. Also Cross Correlation Coefficient in thigh thigh varied across the conditions (F (2, 46) = 4.651, P = .014). CCC for thigh thigh coupling during condition 1 were significantly increased compared to condition 3 ( P = .0 39; Figure 4 5) There was n o difference for CCC in condition 1 versus 2 or condition 1 versus 3 ( P >.05) No effect on Cross Correlation Coefficient in shank shank and foot foot coupling was displayed (P> .05). Table 4 3 illustrates the loading conditions compared to each other for RMS difference and C CC in interlimb couplings.
42 Table 4 1. Comparisons of the loading conditions for gait kinematics Kinematic variables Condition 1 v. 2 Condition 1 v. 3 Condition 2 v. 3 Stride Length Cadence Step Width Swing/Stance Ratio Loaded Swing/Stance Ratio Unloaded Note. = no difference, = increase, = decrease
43 Table 4 2 Comparisons of RMS difference for intralimb couplings N ote. = no difference, = increase, = decrease RMS Difference Condition 1 v. 2 Condition 1 v 3 Condition 2 v. 3 Loaded Thigh shank stance swing Shank Foot stance swing Unloaded Thigh Shank Stance Swing Shank foot Stance Swing
44 Table 4 3 Comparisons of RMS difference and CCC for interlimb couplings RMS difference Condition 1 v. 2 Condition 1 v. 3 Condition 2 v. 3 Thigh Thigh Shank Shank Foot Foot CCC Thigh Thigh Shank Shank Foot Foot Note. = no difference, = increase, = decrease
45 Figure 4 1 Effect of three different loading conditions ( Figure 3 1) on stride length, cadence, and step width. *P< .05
46 Figure 4 2 Effect of three different loading conditions ( Figure 3 1) on swing/stance ratio. P < .05.
47 Figure 4 3 RMS difference in thigh shank coupling during both stance and swing phase for the loaded and unloaded side s *P<. 05.
48 Figure 4 4 RMS difference in shank foot coupling during both stance and swing phase for the loaded and unloaded side s *P<. 05.
49 Figure 4 5 RMS difference and Cross correlation coefficient for thigh thigh coupling over a gait cycle. *P<. 05.
50 CHAPTER 5 DISCUSSION Kinematic Gait P arameters: Hypothesis 1 The aim of this study was to investigate the effect of different loading conditions on temporal spatial gait patterns during treadmill walking for healthy university students Our firs t hypothesis was supported or partially supported for three of the five tests performed related to gait kinematics (Table 4 1). More specifically, Gait pattern was improved when carrying two messenger bags (one on each shoulder) compared to a messenger bag on one shoulder (hanging vertically or draped across the body). Several previous studies have identified the influence of loading on gait kinematics ( Crosbie et al. 1994; Pascoe et al. 1997 ; Cottalorda et al. 2003; Connolly et al. 2008; Birrel & Haslam, 2009 ). Stride length and cadence in normal gait are approximately 1.41 m and 113 steps/min in adult participants respectively (Perry, 1992). O ur values regarding stride length and cadence were less than those of normal walking ; presumably because participants in the current study walked on a treadmill. On a treadmill, individuals show decreased stride length and faster cadence due to short tr eadmill belts ( Cottalorda et al. 2003 ). Accordingly, we observed lower cadence values across conditions during treadmill walking than those of normal gait. In addition, the individuals tested here selected a slower speed (0.8m/s) than normal walking velocity as their preferred walking speed Crosbie and colleagues examined the effect of unilateral load carriage at 10% and 20% of body weight for twenty college students. They reported a decrease in step length and an increase in cadence in response to unilateral carriage while walking barefoot on a flat walkway ( Crosbie et al. 1994) Pascoe et al. (1997) found that stride
51 length was decreased and cadence was increased when carrying a one strap bag, two strap bag, or a one stra p athletic bag compared to no bag. Additionally, these authors did not find a significant difference between u nilateral and bilateral load carriage O ur results in part, support this tendency regarding stride length and cadence and will be discussed shortly However, i n the current study, the no load condition for gait kinematics was not measured and thus was not available for comparison In a more recent study Cottalorda et al. ( 2003 ) evaluated the effect of different met hods of backpack carrying (unilateral and bilateral carriage) while walking on a treadmill on gait kinematics in children. Again, a decrease in stride length and an increase in cadence when carrying a backpack on both shoulders compared to no bag was found, but no difference between one strap and two straps was observed and only a single one strap condition was evaluated Furthermore, Connolly et al. (2008) studied thirty two children under two different load conditions while walking on an ele ctronic walkway (GAITRite system) and reported a decrease in stride length when carrying the backpack loaded with 15% of body weight on one shoulder compared to those without a backpack However, they also reported no difference in stride length between t wo experimental conditions ( carrying a backpack on one shoulder and two shoulders ) Our data were consistent with these previous studies and did not show significant differences in stride length and cadence between unilateral load carriage and bilateral lo ad carriage. T herefore, regardless of whether participants walked overground or on a treadmill, stride length and cadence were not sensitive to symmetric and asymmetric loading. In addition, i t is possible that the mechanics of walking on a treadmill were externally dictated. The velocity of the treadmill was fixed and may
52 preferred walking speed in each condition Thus, these parameters (stride length and cadence) were not influenced by different methods of loa d carriage while walking on a treadmill. However we also evaluated the effect of different unilateral load carriage strategies (condition s 2 and 3) W hen carrying the messenger bag on one shoulder hanging vertically (condition 2), stride length was decrea sed compared to when the participant carried a messenger bag on one shoulder with the bag draped across the trunk to the contralateral hip (condition 3). This result was unexpected, could infer potential benefits related to condition 3, and warrants furthe r research Changes in stride length and cadence during walking are associated with the sagittal plane and may contribute to gait stability. It has been shown that shorter stride length decreases anterior posterior stability ( McAndrew & Dingwell 2012 ). Mo reover, faster cadence may indicate an adaptive strategy to maintain dynamic balance by selecting a proper cadence in response to external constraints ( Arif et al. 2002; Rogers et al. 2008). None of our participants had difficulty completing the walking tasks even though altered stride length and cadence have been related to risk of falling ( Maki, 199 7 ). The shorter stride length and faster cadence observed during condition 2 compared to condition 3 indicate that thi s strategy used for unilateral load carriage could negatively alter walking kinematics and increase risk. In addition, we found altered gait parameters in the frontal plane. Step width during asymmetrical load carriage (conditions 2 and 3) was increased compared to symmetrical load carriage (condition 1). In general, step width in normal walking rang es from 7.1 to 9.1cm (Murray et al. 1964) In the current study, all measurement s of step widths across the conditions were greater than those of normal gait. Several previous
53 researchers have examined different methods of carrying loads in terms of step width. Crosbie et al. (1994 ) reported a significant decrease in step width f or unilateral loading conditions ( 10% and 20% of body weight) compared to a no load condition for male college students and a non significant trend towards an increase in step width for female students. Connolly et al. (2008) observed decreased step w idths while carrying a 10kg backpack on one shoulder compared to without a backpack for children. A lso, a more recent study showed a decrease in step width while carrying loads (10% and 20% of body weight) in one hand compared to no load for healthy adults (Zhang et al. 2009). As stated previously, in our current study, we did not evaluate the no load condition. Thus, in this respect, our data could not be directly compared to previous research. Despite this inconvenience important inferences can be made. In general, unilateral loads shift the center of mass towards the loaded side. Thus, increased step width during asymmetrical loading conditions may indicate an increase in the base of support boundaries to maintain lateral stabilit y during unilateral carriage ( Crosbie et al. 1994; Connolly et al. 2008) Therefore, these alterations in step width may show a compensatory adjustment of shifted COM in response to asymmetric load carriage. To preserve dynamic balance, our participants may have needed the increased step width to compensate for the laterally displaced COM We also found an effect of asymmetrical loading on stance and swing time over a gait cycle. Normal gait consist s of 62% stance phase and 38% swing phase, indicating 0.61 swing /stance ratio ( Kirtley, 2008 ) I n the current study, Swing/stance ratios were measured in three different loading conditions for both loaded and unloaded side s and were slightly below 0.61 for each A h igher swing/stance ratio indicates more swing time
54 and less stance time over a gait cycle and decreased stability ( Berman et al. 1987; Roth et al. 1997; Wu et al. 2000 ) On the loaded side, the swing/stance ratio s for asymmetrical loading (cond ition s 2 and 3) were increased compared to symmetrical loading which indicates more stance time and less swing time over the gait cycle. For the unloaded side, we found an opposite trend indicating that swing/stance ratio s in condition 2 and 3 were decreas ed compared to condition 1. A symmetrical load carriage affected both legs in a complementary manner because during one leg s stance phase the other leg has swing phase over a gait cycle. T he effect of loads on swing / stance ratio or stance and swing time ha s not been investigated in other studies. However, a similar effect on swing and stance time has been seen for obese people ( et al. 2011 ) T he se authors found 5% shorter swing and 3% longer stance for obese individuals compared to lean participants In the current study, the average effective BMI for participants carrying a load of 10% of body weight was increased to 2 5.3 Thus they were classified as overweight (BMI of 25 29.9) but no t obes e (BMI > 30) W e found similar changes on the loaded side which indicate s more stance time to possibly avoid losing dynamic stability Moreover, complementary changes on the unloaded side may be an additional adaptive strategy to maintain dynamic balance during gait. T he changes in both legs indicate an asymmetric gait pattern in terms of swing/stance ratio. T his change in symmetry relative to swing/stance ratio has been reported in hemiplegic gait (Roth et al. 1997). Also, this temporal asymmetry was suggested in patient s with chronic stroke (Patterson et al. 2008). Thus asymmetrical loading appears to cause inverse swing/stance ratio changes in the loaded and unloaded side s Although, t hese alterations in symmetry assist to preserve dynamic balance, ultimately these changes
55 are less stable and this may lead to abnormal walking patterns in response to the asymmetric load on one shoulder. T o conclude, gait patterns were altered by different loading conditions in the current study ( primarily in the frontal plane) Alterations in tempor o spatial parameters during different load conditions may provide insight into adaptive strategies in response to external constraints. T hese alterations may increase the risk for injury in some cases. M ost of the changes in gait patterns were detected in condition 2 compared to the other conditions. Based on our findings, altered gait patterns observed while carrying a messenger bag on one shoulder hanging vertically to the hip were needed to compensate for decreased stability during gait. Limb C oordination: Hypothesis 2 The present study of intralimb and interlimb coordination using CRP aimed to evaluate c oordinative lower extremity mechanism s in response to different loading conditions during treadmill wa l king. Hypothesis 2 was supported by three out of four dependent measures for stance and partially supported for two of four related to swing in terms of RMS for in tra limb coupling ( Table 4 2 ) Also, hypothesis 2 was supported by two out of six dependent measures related to interlimb couplings in terms of RMS and CCC measures (Table 4 3) RMS difference and CCC were used to quantify differences in intralimb and interlimb coordination for the three different loading conditions and indicated that coordination was altered during unilateral load carriage Specifically, t wo average CRP curves in the baseline condition and each carriage condition were compared to evaluate coordinative patterns for the three different loading conditions using RMS and Cross correlation coefficient. While the CCC measure indicates changes in the spatio temporal evolution of CRP patterns, RMS measures show
56 information about the magnitude differences in relative phase be tween the patterns (Haddad et al. 2004). For thigh shank coupling, RMS difference in both loaded and unloaded sides during stance phase were increased in condition 2 and condition 3 compared to condition 1. W e found no difference in RMS in the swin g phase for thigh shank coupling Although, we utilized different experimental conditions (bilateral and unilateral load carriages) than those used by Haddad and colleagues (unilateral load carriage) we can gain insight into the effect of unilateral load carriage. Specifically, s imilar tendencies for RMS differences between no load and unilateral leg loads conditions have been detected in the previous research (Haddad et al. 2004) They utilized six unilateral leg loads (no load, 0.9, 1.8, 2.7, 3.6, and 4.5 kg) during treadmill walking and observed an increase in RMS changes (4 9 ) over both stance and swing phase as the leg load was increased for the loaded limb in thigh shank coupling with no effect on the unloaded side. We also observed RMS changes on the unloaded side in stance and no difference in RMS in swing phase in thigh shank couplings. In part, their findings are in contrast with our res ults due to different methods of carrying loads However RMS difference only represents information on the magnitude of difference between two curves in different loading conditions but does not show which curve is more out of or in phase. Complete CRP c urves provide information regarding how in phase or out of phase two segments are during the entire stance phase. In phase coupling indicates that two segments of the body are temporally aligned regarding three components: angular displacement angular velocity and direction of two segments movement ; non alignment is indicative of out of phase coupling. This additional information provides
57 insight into the coordination patterns utilized in the different conditions tested here (Figures 5 1 to 5 5 ). For example, the CRP pattern in condition 2 (Figure 5 1 ) was more out of phase than normal walking (baseline) in early stance phase (0 20%) for thigh shank coupling in the loaded side. L ess out of phase thigh shank coupling was observed on the lo aded side for asymmetrical loads (condition s 2 and 3) compared to the symmetrical load (condition 1).The majority of the RMS difference in condition 2 for thigh shank coupling o n the loaded side was in mid to late stance (40 90%). Also, RMS changes in cond ition 3 compared to condition 1 result ed from less out of phase coupling during stance (30 60% and 80 100%). T hese RMS changes indicate restricted thigh shank coupling in the loaded side during the unilateral load carriage on one shoulder. We also found sim ilar RMS modification in thigh shank coupling o n the unload ed side. For the two asymmetric loading conditio ns the CRP curves for condition 2 and condition 3 ( F igure 5 2) were less out of phase for thi gh shank coupling compared to condition 1. M ajor changes in condition 2 compared to condition 1 appeared in mid stance (40 60%). Also, RMS changes in condition 3 compared to condition 1 appeared in mid to late stance (30 100%). L ess out of phase thigh shank pattern s have been seen in hemiparetic gai t (Hutin et al. 2010). M oreover, Hutin and colleagues applied an orthotic knee constraint in healthy participants which produc ed a reduction in RMS during swing and stance phase s T h e loss of thigh shank coupling during stance phase indicates one of the altered coordination patterns that may relate to restricted knee flexion during gait. T herefore, asymmetrical loading may contribute to less out of phase movement, altering knee flexion during stance phase in both the loaded and unloaded side compared to symmetrical loading
58 For shank foot coupling, we found significant RMS differences only on the loaded side during both swing and stance phase. These RMS differences also represent part ial information. Further graphical analysis (Figure 5 3 ) revealed that the RMS difference s in condition 2 and 3 result from more out of phase coupling compare d to condition 1. The CRP curves in condition s 2 and 3 during late stance phase (80 100%) show mor e out of phase movement compared to condition 1. T hese two asymmetrical loading conditions contributed to intensified out of phase shank foot coupling on the loaded side during late stance (Figure 5 3). A s ignificant RMS change in condition 3 on the loade d side resulting from changes during early and mid late swing phase ( 0 2 0% and 6 0 90 %) was also observed compared condition 1 which indicate s a more out of phase pattern in condition 3 (Figure 5 4 ). Regarding intralimb coupling, we also detected CCC changes in response to difference loading conditions. Our finding s support previous research (Haddad et al. 2004) that displayed invariance in CCC (all values were greater than 0.99) for the intralimb couplings while carrying a unilaterally applied leg load. Also, these authors showed altered RMS for loaded limb coupling in response to increases in leg load. However, we found an RMS difference in thigh shank coupling on the unloaded side as well as the loaded side. A lso, Haddad et al. (2004) indicated only RMS changes but not where these RMS changes resulted from. A nother interesting finding here is that CRP curves in thigh shank and shank foot display completely different a daptations in response to asymmetric loading. T high shank couplings on both sides during stance were less out of phase, while shank foot coupling showed a more out of phase pattern on the loaded side during both swing and stance with an asymmetrical load compared to symmetric load ing Thus, it is possible that increased
59 out of phase shank foot coupling may be related to increased ankle stiffness during asymmetrical load carriage in the loaded limb which could result in restricted knee movement. T he effect of asymmetric load carriage was also observed for interlimb coordination. A s mentioned before, RMS changes in t high thigh coupling while carrying the asymmetric load in condition 2 were observed More specifically, t hese changes resulted from exaggerated asymmetry in thigh thigh coupling during the gait cycle (Figure 5 5). Also, the CCC value in thigh thigh couplin g was decreased when carrying a messenger bag on one shoulder (condition 3), indicating a higher difference in coordination compared to carrying two messenger bags (one on each shoulder) P revious researchers reported an increase in RMS and a decrease in C CC regarding interlimb couplings in response to unilateral leg loads during treadmill walking (Haddad et al. 2004) T hey observed an increase in RMS and a decrease in CCC (.95 0.7) for thigh thigh, shank shank and foot foot couplings as leg load was increased. H owever, in the current study, increased asymmetry in interlimb coordination was found only for thigh thigh coupling in terms of RMS and CCC measures. In general, smooth ness and symmetry in gait are regarded as normal walking A symmetry duri ng gait has been observed in previous pathological gait research as stroke, s, hemiplegia and cerebral palsy (Roth et al. 1997; Patterson et al. 2008; Johnsen et al. 2009; Meyns et al. 2012 ) In these previous studies, researchers have focused on clinical treatment s to improve the asymmetry in gait for these patients. A symmetry during gait as observed here, may be considered potentially injurious with symptoms beyond the capacity of loc omotor system.
60 T he results of the current study suggest a variety of adaptation s in intralimb and interlimb coordination in response to symmetric and asymmetric load carriage. W e expected that altered coordinative patterns in the lower extremities would be displayed during asymmetrical load carriage. A s indicated before, changes in intralimb and interlimb coordination were observed for the asymmetric al loading conditions compared to symmetric loading condition. However, the two diffe rent asymmetrical conditions did not show any difference in interlimb and intralimb couplings. We observed abnormal patterns in thigh shank, shank foot, and thigh thigh coordination. Based on our finding s we recommend people avoid carrying a m essenger bag on one shoulder ( condition 2 or 3) in order to decrease abnormal limb coordination in daily activities T hese alterations may provide researchers with preliminary knowledge concerning diverse gait adaptations caused by external constraints The adaptation s in limb coordination during asymmetrical load carr i age should be further investigated as they may be indicative of the possibility for acute and /or chronic joint injury and pain Furthermore, asymmetric load carriage may have potential to alter coordinative mechanisms in the lower extremities which may be associated with the risk of falling in taxing circumstances (e.g. slope, stairs, wet floors, etc .) Our results provide a picture of adaptive mechanisms of locomotor systems under various constraints, which may enable us to educate at risk individuals ( e.g., the elderly and children) on the dangers of abnormal gait patterns Limitation of S tudy In our study, arm movement was constr ained across the previously referenced conditions because clear and accurate collection of kinematic data in the laboratory environment required participants to cross their arms. However, arm movements are indispensable parts of human locomotion that play an important role for contralateral
61 limb movement s (Eke Okoro et al. 1997). In addition, a s alluded to previously, we evaluated individuals walking at a fixed velocity on a treadmill. T hus, they could not alter their walking velocity. However, changing walking speed in response to different loading conditions could be a n important adjustment to preserve dynamic balance during these conditions. Subsequen t work could involve calculating a preferred walking pace in each experimental condition. Finally the difference s between over ground and treadmill walking should be considered. O n a treadmill, altered gait patterns have been observed because of short tre admill belts ( Cottalorda et al. 2003 ). T hus, it is possible that different coordinative patterns during overground walking may exist F urther, treadmill walking may have limited application to real world conditions when people carry loads for work or recreation
62 Figure 5 1. Mean CRP curves in thigh shank on the loaded side during stance phase for baseline (no load) and each experimental condition (n=24). T high shank in l oaded side
63 Figure 5 2 Mean CRP curves in thigh shank on the unloaded side during stance phase for baseline (no load) and each experimental condition (n=24). T high shank in unl oaded side
64 Figure 5 3 Mean CRP curves in shank foot on the loaded side during stance phase for baseline (no load) and each experimental condition (n=24). Shank foot in loaded side
65 Figure 5 4 Mean CRP curves in shank foot on the loaded side during swing phase for baseline (no load) vs condition 1 and 3 (n=24). Shank foot in loaded side sidn \ ssssssswing
66 Figure 5 5 Mean CRP curves in thigh thigh coupling over a gait cycle for baseline (no load) and each condition (n=24). Thigh thigh
67 LIST OF REFERENCES An D H, Yoon J Y, Yoo W G, Kim K M. Comparisons of the gait parameters of young Korean women carrying a single strap bag. Nurs Health Sci 2010;12(1):87 93. Arif M, Ohtaki Y, Ishihara T, Inooka H. Walking gait stability in young and elderly people and improvement of walking stability using optimal cadence. In: Micromechatronics and Human Science, 2002. MHS 2002. Proceedings of 2002 International Symposium on .; 2002:245 251. Berman AT, Zarro VJ Bosacco SJ, Israelite C. Quantitative gait analysis after unilateral or bilateral total knee replacement. J Bone Joint Surg Am 1987;69(9):1340 1345. Birrell SA, Haslam RA. The effect of military load carriage on 3 D lower limb kinematics and spatiotempo ral parameters. Ergonomics 2009;52(10):1298 1304. Swider J. Impact of excess body weight on walking at the preferred speed. Acta Neurobiol Exp (Wars) 2011;71(4):528 540. Connolly BH, Cook B, Hunter S. Effects of backpack carriage on gait parameters in children. Pediatr Phys Ther 2008;20(4):347 355. Cottalorda J, Rahmani A, Diop M. Influence of school bag carrying on gait kinetics. J Pediatr Orthop B 2003;12(6):357 364. Crosbie J, Flynn W, Rutter L. Effect of side load carriage on the kinematics of gait. Gait & Posture 1994;2(2):103 108. DeVita P, Hong D, Hamill J. Effects of asymmetric load carrying on the biomechanics of walking. J Biomech 1991;24(12):1119 1129. Eke Okoro ST, Gregoric M, Larss on LE. Alterations in gait resulting from deliberate changes of arm swing amplitude and phase. Clin Biomech (Bristol, Avon) 1997;12(7 8):516 521. Forner Cordero A, Levin O, Li Y, Swinnen SP. Principal component analysis of complex multijoint coordinative movements. Biological Cybernetics 2005;93:63 78. Fowler NE, Rodacki ALF, Rodacki CD. Changes in stature and spine kinematics during a loaded walking task. Gait Posture 2006;23(2):133 141. Grimmer KA, Williams MT, Gill TK. The associations between adolesc ent head on neck posture, backpack weight, and anthropometric features. Spine 1999;24(21):2262 2267. Grimmer K, Williams M. Gender age environmental associates of adolescent low back pain. Appl Ergon 2000;31(4):343 360.
68 Haddad JM, van Emmerik REA, Whittl esey SN, Hamill J. Adaptations in interlimb and intralimb coordination to asymmetrical loading in human walking. Gait Posture 2006;23(4):429 434. Hamill J, van Emmerik RE, Heiderscheit BC, Li L. A dynamical systems approach to lower extremity running inju ries. Clin Biomech (Bristol, Avon) 1999;14(5):297 308. pathological processes and implications for treatment. Scoliosis 2006;1(1):3. Hutin E, Pradon D, Barbier F. Lower l imb coordination patterns in hemiparetic gait: factors of knee flexion impairment. Clin Biomech (Bristol, Avon) 2011;26(3):304 311. Ikeda ER, Cooper L, Gulick P, Nguyen P. The metabolic cost of carrying a single versus double strap golf bag. J Strength Cond Res 2008;22(3):974 977 Johnsen EL, Mogensen PH, Sunde NA, stergaard K. Improved asymmetry of gait in treated with bilateral deep brain stimulation in the subthalamic nucleus. Mov. Disord. 2009;24(4):590 597. Kinoshita H. Effects of different loads and carrying systems on selected biomechanical parameters describing walking gait. Ergonomics 1985;28:1347 1362. Kirtley C. History of the study of locomotion: The modern er a. From http://www.univie.ac.at/cga/history/modern.html. 2008 Korovessis P, Koureas G, Zacharatos S, Papazisis Z. Backpacks, back pain, sagittal spinal curves and trunk alignment in adolescents: a logistic and multinomial logistic analysis. Spine 2005;3 0(2):247 255. Kurz M and Stergiou N Applied dynamic systems theory for the analysis of movement. Legg SJ, Cruz CO. Effect of single and double strap backpacks on lung function. Ergonomics 2004;47(3):318 323. Legg SJ, Ramsey T, Knowles DJ. The metabolic c ost of backpack and shoulder load carriage. Ergonomics 1992;35(9):1063 1068. Macias BR, Murthy G, Chambers H, Hargens AR. Asymmetric loads and pain associated with backpack carrying by children. J Pediatr Orthop 2008;28(5):512 517. Maki BE. Gait changes in older adults: predictors of falls or indicators of fear. J Am Geriatr Soc 1997;45(3):313 320.
69 Mann R. Bioemchancis. In M. H. Jahss (Ed.), Disorders of the foot (pp. 37 67). Philadelphia: W. B. Saunders Company, 1982. Marras W.S. and Granata K.P., Spin al loading during trunk lateral bending motion, J Biomech 30 (1997), pp. 697 703 Matsuo T, Hashimoto M, Koyanagi M, Hashizume K. Asymmetric load carrying in young and elderly women: relationship with lower limb coordination. Gait Posture 2008;28 (3):517 520. May B, Tomporowski PD, Ferrara M. Effects of backpack load on balance and decisional processes. Mil Med 2009;174(12):1308 1312. McAndrew Young PM, Dingwell JB. Voluntary changes in step width and step length during human walking affect dynami c margins of stability. Gait & posture 2012. Meyns P, Van Gestel L, Bruijn SM. Is interlimb coordination during walking preserved in children with cerebral palsy? Res Dev Disabil 2012;33(5):1418 1428. Miller RH, Chang R, Baird JL, Van Emmerik REA, Hamill J. Variability in kinematic coupling assessed by vector coding and continuous relative phase. J Biomech 2010;43(13):2554 2560. Murray MP, Drought AB, Kory RC. Walking Patterns of Normal Men. J Bone Joint Surg Am, 46 335 360, 1964. Negrini S, Carabalona R, Sibilla P. Backpack as a daily load for schoolchildren. The Lancet 1999;354:1974. Negrini S, Negrini A. Postural effects of symmetrical and asymmetrical loads on the spines of schoolchildren. Scoliosis 2:8 8. Neumann DA. Hip abductor muscle activity in persons with a hip prosthesis while carrying loads in one hand. Phys Ther 1996;76(12):1320 1330. Pascoe DD, Pascoe DE, Wang YT, Shim DM, Kim CK. Influence of carrying book bags on gait cycle and posture of youths. Ergonomics 1997;40(6):631 641. Patter son KK, Parafianowicz I, Danells CJ. Gait asymmetry in community ambulating stroke survivors. Arch Phys Med Rehabil 2008;89(2):304 310. Pau M, Corona F, Leban B, Pau M. Effects of backpack carriage on foot ground relationship in children during upright stance. Gait Posture 2011;33(2):195 199. Perry J. Gait analysis: Normal and pathological function Thorofar, NJ: Slack Incorprated. 1992.
70 Plotnik M, Giladi N, B disease related to asymmetric motor function? Annals of Neurology 2005;57(5):656 663. Reisman DS, Block HJ, Bastian AJ. Interlimb Coordination During Locomotion: What Can be Adapted and S tored? Journal of Neurophysiology 2005;94(4):2403 2415. Roaf R. Vertebral growth and its mechanical control. J Bone Joint Surg Br 1960;42 B:40 59. Rogers HL, Cromwell RL, Grady JL. Adaptive changes in gait of older and younger adults as responses to cha llenges to dynamic balance. J Aging Phys Act 2008;16(1):85 96. Roth EJ, Merbitz C, Mroczek K, Dugan SA, Suh WW. Hemiplegic gait. Relationships between walking speed and other temporal parameters. Am J Phys Med Rehabil 1997;76(2):128 133. Sakas DE, Boviat sis EJ, Stavrinou LC. Backpack treatment for camptocormia. Mov. Disord. 2010;25(13):2254. Simpson KM, Munro BJ, Steele JR. Backpack load affects lower limb muscle activity patterns of female hikers during prolonged load carriage. J Electromyogr Kinesiol 2 011;21(5):782 788. Simpson KM, Munro BJ, Steele JR. Effect of load mass on posture, heart rate and subjective responses of recreational female hikers to prolonged load carriage. Appl Ergon 2011;42(3):403 410. Stergiou N. Innovative Analyses of Human Movement Human Kinetics; 2004. Sutherland DH, Kaufman KR, and Moitoza JR Kinematics of normal human walking. In: Rose J, and Gamble JG, Editors, Human walking, Williams & Wilkins, Baltimore, MD 1994: 23 45. Varlet M, Richardson MJ. Computation of continu ous relative phase and modulation of frequency of human movement. J Biomech 2011;44(6):1200 1204. Vicky Uhland. Bags carry the accoutrements of 21st Century life. Available at: http://www.wearablesmag.com/wearablesbusiness/mag/apparel_bags_carry_acco utrements/index.html. Wendlova J. The importance of carrying a backpack in the rehabilitation of osteoporotic patients (biomechanical analysis). Bratisl Lek Listy 2011;112(1):41 43. Whittfield JK, Legg SJ, Hedderley DI. The weight and use of schoolbags in New Zealand secondary schools. Ergonomics 2001;44(9):819 824.
71 Wu W L, Su F C, Cheng Y M. Gait analysis after ankle arthrodesis. Gait & Posture 2000;11(1):54 61. Zhang XA, Ye M, Wan g CT. Effect of unilateral load carriage on postures and gait symmetry in ground reaction force during walking. Comput Methods Biomech Biomed Engin 2010;13(3):339 344. Zultowski I, Aruin A. Carrying loads and postural sway in standing: the effect of load placement and magnitude. Work 2008;30(4):359 368.
72 BIOGRAPHICAL SKETCH Junsig Wang was born in Seoul, Korea After receiving his Bachelor of Education Degree in physical education from Kyung Hee University he attended the University of in the fall of 2010 He received a Master of Science degree in applied kinesiology and physiology (APK) with a concentration in Biobehavioral Science from the University of Florida in August 2012