Group Title: Journal of NeuroEngineering and Rehabilitation 2009, 6:18
Title: Pilot study of Lokomat versus manual-assisted treadmill training for locomotor recovery post-stroke
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Title: Pilot study of Lokomat versus manual-assisted treadmill training for locomotor recovery post-stroke
Series Title: Journal of NeuroEngineering and Rehabilitation 2009, 6:18
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Creator: Westlake KP
Patten C
Publication Date: 39976
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Rehabilitation BioMed (


Pilot study of Lokomat versus manual-assisted treadmill training
for locomotor recovery post-stroke
Kelly P Westlake' and Carolynn Patten*2'3

Address: 'Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA, 2Brain Rehabilitation
Research Center, Malcolm Randall VA Medical Center, Gainesville, Florida, USA and 3Department of Physical Therapy, University of Florida,
Gainesville, Florida, USA
E-mail: Kelly P Westlake; Carolynn Patten*
*Corresponding author


Published: 12 June 2009
journal of NeuroEngineering and Rehabilitation 2009, 6:18 doi: 10.I 186/1743-0003-6-18

Received: 4 December 2008
Accepted: 12 June 2009

This article is available from:
2009 Westlake and Patten; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: While manually-assisted body-weight supported treadmill training (BWSTT) has
revealed improved locomotor function in persons with post-stroke hemiparesis, outcomes are
inconsistent and it is very labor intensive. Thus an alternate treatment approach is desirable.
Objectives of this pilot study were to: I) compare the efficacy of body-weight supported treadmill
training (BWSTT) combined with the Lokomat robotic gait orthosis versus manually-assisted
BWSTT for locomotor training post-stroke, and 2) assess effects of fast versus slow treadmill
training speed.
Methods: Sixteen volunteers with chronic hemiparetic gait (0.62 0.30 m/s) post-stroke were
randomly allocated to Lokomat (n = 8) or manual-BWSTT (n = 8) 3x/wk for 4 weeks. Groups were
also stratified by fast (mean 0.92 0.15 m/s) or slow (0.58 0.12 m/s) training speeds. The primary
outcomes were self-selected overground walking speed and paretic step length ratio. Secondary
outcomes included: fast overground walking speed, 6-minute walk test, and a battery of clinical
Results: No significant differences in primary outcomes were revealed between Lokomat and
manual groups as a result of training. However, within the Lokomat group, self-selected walk speed,
paretic step length ratio, and four of the six secondary measures improved (p = 0.04-0.05, effect
sizes = 0.19-0.60). Within the manual group, only balance scores improved (p = 0.02, effect size =
0.57). Group differences between fast and slow training groups were not revealed (p > 0.28).
Conclusion: Results suggest that Lokomat training may have advantages over manual-BWSTT
following a modest intervention dose in chronic hemiparetic persons and further, that our training
speeds produce similar gait improvements. Suggestions for a larger randomized controlled trial
with optimal study parameters are provided.

Stroke is the leading cause of serious, chronic disability
in the United States and Canada. While two-thirds of
people who suffer a stroke regain ambulatory function,
the resulting gait pattern is typically asymmetrical, slow,

and metabolically inefficient [1,2]. These characteristics
are associated with difficulty advancing and bearing
weight through the more affected limb, leading to
instability and an increased risk of falls [3]. Secondary
impairments, including muscle disuse and reduced

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

cardiorespiratory capacity, often contribute to further
functional declines in gait. Hence, improved walking is
one of the most frequently articulated goals of rehabi-
litation and interventions that effectively enhance
locomotor function are essential to improve quality of
life for many stroke survivors and their families [4,5].
Nevertheless, the effectiveness of locomotor training still
remains unclear and the need to conduct randomized
controlled trials to definitively answer this question is
paramount. To best determine the key parameters of
such a large-scale study, preliminary data must first be
collected in the form of a pilot study.

Manually-assisted body-weight supported treadmill
training (BWSTT) is a contemporary approach to gait
rehabilitation wherein an individual walks on a tread-
mill with body-weight partially supported by an over-
head harness. One to three therapists/trainers manually
facilitate hemiparetic limb and trunk control in an effort
to normalize upright, reciprocal stepping and dynamic
postural control. Advantages of this approach are that
little to no ambulatory function is required to initiate
locomotion and early post-stroke training effects are
transferred to improvements in overground gait includ-
ing: symmetry, speed, and endurance as well as motor
impairment and balance scores [6,7]. These positive
outcomes can be maintained even at 6 months post-
locomotor training [8]. However, because locomotor
training involves repetition of hundreds of steps within
one session, facilitation of a symmetrical, patterned gait
can be very labor intensive for both therapists) and
participant and further, presents a non-trivial risk of
injury to the trainers. Moreover, the repetition of
kinematically consistent stepping patterns is hindered
by inconsistencies in motor performance of the thera-
pists assisting movement. Conflicting evidence within 15
randomized controlled trials comparing BWSTT and
traditional gait training (i.e. overground gait training,
motor relearning) in persons post-stroke highlight the
difficulty in interpreting the effectiveness of manually
applied cues during repetitive stepping [9].

In response to the challenges presented in administering
manual-BWSTT, robotic devices, such as the Lokomat@
(Hocoma, Inc., Zurich, Switzerland), have recently
emerged as a means to automate locomotor training in
neurorehabilitation. Using robotic assistance, an exoske-
leton facilitates a bilaterally symmetrical gait pattern as
the individual actively attempts to advance each limb
while walking on the treadmill. The preprogrammed
walking pattern corresponds with normal gait kinematics
including: gait cycle timing (i.e. stance vs. swing phase),
inter-limb and inter-joint coordination, appropriate
limb loading, and afferent signaling [10]. Animal models
have demonstrated that afferent signals derived from

limb movement and loading converge at the level of the
spinal cord to trigger and control locomotor pattern
generators (LPGs) [11,12]. Previous work in persons
with spinal cord injuries underscores the importance of
the accuracy of relevant timed peripheral inputs to
induce changes in locomotor function [13]. Accordingly,
the rhythmic and repetitive stepping pattern provided by
robotic assistance, combined with active limb loading
and kinematic consistency has been shown to promote
plasticity of LPGs at the spinal cord level [14] as well as
supraspinal structures [15]. Still, despite recent interest
in automated locomotor training, there remains very
little evidence to support the superiority of this
technique over traditional gait training.

Previous comparisons between robotic-BWSTT and
manual-BWSTT, overground gait training, and tradi-
tional approaches result in equivocal findings based, in
part, on differences in outcome measures, subject
characteristics, and gait training protocols [16-20].
However, separation of the general effects of locomotor
training from true automated training effects requires
standardization of BWSTT parameters, i.e. BWS percen-
tage and stiffness, treadmill speed, and use of handrails
[21], and a comparison between the application of
manual or robotic limb guidance with the intent of
approximating normal gait kinematics in a well-defined
subject population. In controlling these variables, we
hypothesize that Lokomat training will produce greater
improvements in gait speed and symmetry than manual

Extending the notion of task-specificity underlying both
Lokomat and manual-BWSTT, one particular variable of
interest is training speed. If the therapeutic goal is
increased overground walking speed, then training must
occur at speeds that exceed habitual overground walking
speed for a person with hemiparesis. The majority of the
current models of the Lokomat robotic orthosis offer
treadmill belt speeds up to 0.83 m/s (3 km/h), thus it is
yet unknown whether training at higher Lokomat speeds
produces similar positive gait changes as revealed in
earlier studies [8,22]. Here, we hypothesize that the
addition of external timing cues and kinesthetic input
induced by Lokomat training and manual BWSTT at
training speeds of up to 1.4 m/s (5 km/h) will produce
greater improvements in spatio-temporal gait para-
meters, postural control, and clinical outcomes than
groups trained at slower speeds.

Objectives of this pilot study were to: 1) compare the
efficacy of Lokomat versus manual assisted-BWSTT in
persons with chronic locomotor deficits post-stroke and
2) probe the effect of locomotor training at speeds
corresponding with overground gait in non-disabled

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

individuals to habitual self-selected walking speed in
persons post-stroke. Since self-selected overground gait
speed and step length symmetry are important indicators
of locomotor performance, and further, are related to
function and quality of life following stroke [23,24],
these variables were selected as our primary variables of
interest. Secondary outcomes included fast overground
walking speed, a battery of clinical and functional
measures, and a quality of life indicator.

Sixteen persons with hemiparesis resulting from a single
cortical or subcortical stroke (confirmed by CT or MRI)
greater than 6 months prior to the study, who were
categorized as at least unlimited household ambulators
(e.g. > 0.3 m/s) [4] participated. Exclusion criteria
included: 1) unstable cardiovascular, orthopedic, or
neurological conditions, 2) uncontrolled diabetes that
would preclude exercise of moderate intensity, or 3)
significant cognitive 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
Institutional Review Board and all participants provided
written, informed consent prior to study involvement.

Allocation Procedures
In an effort to achieve our primary research goal,
participants were randomized into either a Lokomat
(n = 8) or manual (n = 8) group using a computer-
generated random order. To reach our secondary goal, an
equal number of participants within each group were
randomly assigned to either a fast (n = 8) or slow (n = 8)
training group. The randomization list was overseen by
one of the investigators (CP) who had no contact with
participants until group assignment was revealed.
Further, group assignment was not revealed to study
personnel until the participant was consented and
baseline testing was complete.

Both groups received 12 sessions (3x/wk over 4 weeks)
involving 30 min of stepping per session. At least one 2-
3 minute break was provided after 15 min. Total set-up
and treatment time never exceeded 1 hr. Training speeds
were maintained below 0.69 m/s (2.5 km/h) in the slow
groups and above 0.83 m/s (3 km/h) in the fast groups.
Within the fast groups, locomotor training was either
started at 0.83 m/s or progressed to this speed as early as
possible (e.g. by Session 3) while maintaining gait
quality, i.e. symmetrical, foot clearance, without knee
buckling. Treadmill speed was progressed in 0.2 km/hr
increments approximately every 5 min as long as the

above-mentioned gait quality was observed by the
therapists. If a new high speed could not be maintained
for an extended period, training would ensue in 2-3
minute intervals at the higher speed followed by 2-3
minutes at a lower speed. BWS was initiated at 35%. The
Lokomat system used for this study includes the Lokolift,
a compliant, electromechanical body-weight support
system that monitors and adjusts unweighting in real
time to maintain BWS at the prescribed level. This BWS
system contrasts with the stiff, counterweighted support
system used in the original Lokomat models. A
compliant system adjusts to the participant's center of
gravity throughout the gait cycle, enabling vertical pelvic
movement similar to overground gait, supporting
symmetrical movement and producing kinetics similar
to overground walking [21,25]. If the maximal treadmill
speed, 0.69 m/s (2.5 km/h) in the slow group or 1.4 m/s
(5 km/h) in the fast group, was reached, BWS was
reduced in increments of 5% as long as gait quality was
maintained. Our goal during training was to improve
gait kinematics. To achieve this objective, all participants
trained without an ankle-foot orthosis, assistance was
reduced once safety was no longer a concern, and rest
periods were provided if gait quality was noted to
deteriorate. In addition, handrail use has been shown to
significantly alter the gait pattern and thus was strongly
discouraged [25].

Participants assigned to the Lokomat group trained in a
robotic orthosis. Thigh and leg straps secured the
Lokomat exoskeleton to the participant; motors on
each robotic leg facilitated movement of the hip and
knee joints with trajectories programmed by the manu-
facturer based on a single, healthy individual's gait
pattern. Only when necessary to maintain foot clearance,
the ankle was maintained in neutral dorsiflexion by
means of an elastic foot strap. Force sensors within the
Lokomat hip and knee joints provided output on a visual
display that was monitored by the treating physical
therapist. In an effort to maintain consistency in training
parameters, Lokomat assistance was provided at 100%
bilateral guidance force for all participants throughout
all training sessions. Participants were provided verbal
encouragement to actively step in conjunction with the
movement presented by the Lokomat.

Participants in the manual-BWSTT group were treated by
1-2 skilled physical therapists/trainers who provided
manual guidance of the more affected limb, trunk
stabilization/alignment, and verbal and visual cues to
normalize stepping kinematics. Our intent in using this
number of therapists was to mimic clinic feasibility and
training in previous reports [20]. The target gait pattern
included: adequate trunk alignment, weight shift, accep-
tance to and from the paretic limb and temporal

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

symmetry between limbs. The treating therapist indivi-
dualized treatment to facilitate trunk and limb control
throughout the gait cycle. Common cues included
coaching to: increase plantarflexion propulsion and/or
hip flexion at swing initiation, increase dorsiflexion and
knee extension at heel strike, and maintain neutral knee
alignment (i.e. avoid hyperextension) at midstance. A
second trainer provided pelvic stabilization and assis-
tance with weight shift/acceptance as needed. Partici-
pants in both groups were provided visual feedback via a
full-length mirror placed at the front of the treadmill.

Participants were assessed before and after the 4-week
intervention. Self-selected overground walking speed
and fast overground walking speed were recorded using
a 4.3 m GaitRite mat (CIR Systems, Havertown,
Pennsylvania, USA). Participants walked an additional
0.5 m on both ends of the walkway to allow for
acceleration and deceleration and were instructed to
walk either: "as if taking a comfortable walk in the park"
for self-selected walking speed or "as if they were in the
middle of the intersection and the light had just changed
to red" for fast walking speed. The mean of 3 trials was
calculated. Step length of the paretic (P) and nonparetic
(NP) limb was also recorded and later used to calculate
absolute (ABS) step length asymmetry during self-
selected walking speed as follows:

SLRabs = ABS[1- (P step lengh/ NP step lengh)]

This calculation is a modification of the paretic step
length ratio (SLR) [26] and can range from 0 to 1, with
an index of 0 reflecting perfect symmetry. The 6-minute
walk test was recorded as a measure of gait endurance.
Participants were instructed to cover as much distance as
possible within a 6-minute period while walking safely.
This test was completed along a level carpeted corridor
with one turn-around point every 39 meters. For all
overground gait assessments, ambulation without an
assistive device or lower extremity orthoses was encour-
aged. However, use of these assistive devices was allowed
if deemed necessary for safety. Device usage was
consistent between pre- and post-testing.

Secondary outcomes were selected to target impairment,
activity, and participation according to the World Health
Organization classifications. Motor impairment was
evaluated with the lower extremity Fugl-Meyer assess-
ment, which is a valid and reliable measure in persons
post-stroke [27,28]. Activities were assessed with the
short physical performance battery and the Berg Balance
Scale. The short physical performance battery produces a
summary score (range 0-12) reflecting scores on 3 timed
tasks: walking 8-ft, rising from a chair 5 times, and

maintaining a static posture (feet together, semi-tandem,
tandem) [29]. Good to excellent reliability and pre-
dictive validity have been demonstrated for these tests
[30,31]. The Berg Balance Scale is comprised of 14 static
and dynamic balance tasks with a maximum score of 56.
This measure demonstrates good reliability and validity
in a population post-stroke [32,33]. Participation in life
events was assessed using the Late Life Function and
Disability Instrument (LLFDI) [34], which is composed
of a disability section assessing limitation and frequency
of performance and a function section measuring
difficulty in performing certain physical tasks. Good
reliability and validity has also been demonstrated for
this measure in a population with a range of functional
limitations [35,36].

Data Analysis
Statistical analyses were conducted using SPSSv15.0
(SPSS, Inc., Chicago, Illinois, USA). Given the small
sample size, non-parametric statistics were used. Baseline
characteristics between groups were compared using the
Mann-Whitney U test for continuous and ordinal
variables and the Fisher's exact test for categorical
variables. Between group comparisons (Lokomat vs.
Manual groups and Fast vs. Slow Training groups) were
assessed with the Mann-Whitney U-test using pre-post
change scores in ordinal variables. Within group
comparisons (Pre vs. Post training) were assessed using
the Wilcoxon Signed Ranks Test. Statistical significance
was established at a < 0.05.

To determine whether a statistically significant difference
is of practical concern, effect sizes and percent change
were calculated. Effect sizes were calculated as the
difference between the means of the two groups
(Lokomat and manual) or between the mean pre-test
and post-test values of the same group divided by the
common standard deviation (SD) at pre-test. Results
were interpreted following standards established by
Cohen [37] where 0.2 is indicative of a small effect,
0.5 a medium, and 0.8 a large effect size.

All sixteen participants completed the study and the
twelve training sessions were well tolerated with two
exceptions. First, following the eleventh session, one
participant in the manual group complained of ankle
pain on the hemiparetic side and failed to complete the
final training session. Second, despite using a regular
rotation of two treating therapists, one therapist suffered
a repetitive strain injury of the rotator cuff while training
the third manual group participant. Participant char-
acteristics are enumerated in Table 1. Group equivalency
(i.e. Lokomat vs. manual and fast vs. slow) was

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

Table I: Baseline characteristics and training parameters

Lokomat Manual p value
(n =8) (n = 8)

Age, mean (SD), y 58.6 (16.9) 55.1 (13.6) 0.72a
Women, n (%) 2 (25) 1 (12.5) 1.0b
Time since stroke, mean 43.8 (26.8) 36.8 (20.3) 0.72a
(SD), mo
Stroke location, n
MCA territory (multiple 3 4 1.0b
Frontal lobe 0 I 1.0b
Temporoparietal lobe I 0 1.0b
Parietal lobe I I I.0b
Basal Ganglia 3 I I.0b
Thalamus 0 I I.0b
Pons 0 I 1.0b
Type of Stroke, n
Ischemic 3 5 1.0b
Hemorrhagic 5 3 1.0b
Left sided hemiparesis, n 4 5 1.0b
LE Fugl-Meyer total score, 83.3 (7.3) 80.6 (6.3) 0.13"
mean (SD)
Self-selected walking speed, 0.62(0.31) 0.62 (0.28) 0.80a
mean (SD), m/s
Training speed, 0.82 (0.2) 0.67 (0.2) 0.16"
mean (SD), m/s
Training BWS, mean (SD) 29.4 (5.9) 31 (9.1) 0.28"

aMann-Whitney U test; bFisher's exact test.

established with no significant baseline differences, p >
0.13. In the Lokomat group removal of the foot strap was
possible in 3 participants. One participant advanced to
walking without the foot strap for approximately 54% of
sessions, while two additional participants advanced to
no foot strap for 25% of sessions.

Our first aim of this pilot study was to compare the
effectiveness of Lokomat versus manual-assisted BWSTT
on gait-related outcomes. Overall results revealed no
significant differences between Lokomat and manual
training group improvements on self selected walk
speed, p = 0.72, absolute paretic step length ratio, p =
0.28, or secondary variables, p = 0.54-0.96. However,
within the Lokomat group, a greater number of variables
demonstrated significant pre- vs. post-test differences
compared with the manual group (Table 2).

Although an equal number of participants (n = 7) produced
a training related increase in self-selected overground
walking speed in each group, a significant difference, p =
0.04, was revealed only in the Lokomat group with a pre-
post intervention difference of 0.10 m/s and an effect size of
0.32 which contrasted with a 0.03 m/s difference and 0.11
effect size in the manual group (Figure 1A; Table 2).

Table 2: Group Comparisons of selected outcomes

Variable Lokomat Group (n = 8) Manual Group (n = 8)

Pre-Test Post-Test Pre-Test Post-Test

SSWS (m/s) 0.62 0.31 0.72 0.38* 0.62 0.28 0.65 0.29
(0.26-1.04) (0.3-1.38) (0.24-0.91) (0.30-1.02)
FWS (m/s) 0.87 0.55 0.96 0.66* 0.72 0.37 0.70 0.33
(0.32-1.85) (0.33-2.28) (0.26 1.2) (0.35-1.13)
6 MWT (m) 267.3 187.2 278.1 176.5 234.3 1 141.2 212.4 113.5
(71-625.5) (89.3-638.0) (66.4-452.7) (86.5-362.9)
SLRabs 0.53 0.58 0.37 0.46 0.39 0.37 0.34 0.35
(0.03-1.87) (0.06-1.46) (0.05-1.10) (0.02-1.04)
LE FM (/35) 23.0 4.3 25.6 5.0 21.4 5.1 22.4 5.2
(15-28) (19-34) (14-29) (14-29)
SPPB (/12) 6.9 3.4 7.9 3.2* 7.8 3.0 8.5 3.1
(2-12) (4-12) (4-12) (4-12)
BBS (/56) 46.9 7.5 48.3 6.8 47.0-7.0 51.0-5.4 t
(38-56) (41-56) (38-55) (40-56)
Frequency 52.6 8.1 52.8 7.9 49.7 1 .4 53.5 10.2
(/100) (41.4-65.1) (41.4-62.3) (29.2-70.6) (35.2-66.7)
Limitation 59.4 7.0 62.3 8.5 61.6 9.1 66.4 10.2
(/100) (49.2-69.2) (49.9-71.3) (46.4-75.6) (47.9-77.6)
Function 51.3 7.7 52.0 8.6 48.6 6.0 54.1 4.8
(/100) (43.1-64.0) (42.5-66.8) (41.9-58.7) (46.1-61.6)

Note: values are mean SD (range)
*Pre-post difference within Lokomat group, p < 0.05; t difference within manual group, p < 0.05
Abbreviations: SSWS = self selected walking speed; FWS = Fast walking speed; 6 MWT = 6 minute walk test; SLRabs = Absolute step length ratio;
LE FM = Lower extremity Fugl-Meyer; SPPB, short physical performance battery; BBS = Berg Balance Scale; LLFDI = late life function and disability

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

E 04

Manual Robot

Figure I
Medians and lower and upper quartiles for pre-post
differences in the manual and Lokomat group. A. Self-
selected walk speed. B. Absolute step length ratio (negative
change scores represent a shift towards symmetrical step
lengths). Extreme values are greater than 3 times the
interquartile distance.* Significant difference only within the
Lokomat group (p < 0.05).

Absolute paretic step length ratio (SLRabs) during self-
selected overground walking speed was also significantly
reduced (i.e. closer to an SLRabs of 0) from pre- to post-
test in the Lokomat group, p = 0.05, effect size 0.26,
reflecting improved symmetry in 6 of 8 Lokomat group
participants (Figure 1B; Table 2).

With the exception of the 6-minute walk test and LLFDI,
p > 0.16, all secondary measures revealed significant
improvements within the Lokomat group, yet only one
improvement was noted in the manual group (Table 2).
Fast overground walk speed improved from pre- to post-
training in 6 of 8 Lokomat participants, p = 0.05, with a
small effect size of 0.15 (Figure 2A). Lower extremity
Fugl-Meyer score improvements were also noted, p =
0.04, with an effect size of 0.60 and higher scores in 5 of
8 Lokomat group participants (Figure 2B). Similarly,
short physical performance battery scores were improved
in the Lokomat group, p = 0.04, with an effect size of
0.29 and improvements in 5 of 8 participants. Berg
Balance Scale scores significantly improved in both the
Lokomat group, p = 0.04, effect size 0.19 (5 participants
improved), and manual group, p = 0.02, effect size 0.57
(7 participants improved) (Figure 2C).

Participation in life events, as measured by the LLFDI,
also demonstrated improvements, but statistical differ-
ences were attained only as a main effect of visit (i.e. pre
vs. post) and were not specific to either the Lokomat or
manual-BWSTT group. The disability component reflects
two dimensions: limitation and frequency. Our data
revealed that participants felt less limited in their
participation in activities at home and in the commu-
nity, p = 0.02, with an effect size of 0.49. Interestingly,
the frequency of self-reported participation in these tasks
remained unchanged from pre-test to post-test, p > 0.11.
Participants also perceived less difficulty in terms of the

t i "I- ------ ------

S -300-
Manual Robot Manual Robot
Figure 2
Medians and lower and upper quartiles for pre-post
differences in the manual and Lokomat group. A. Fast
Walk speed. B. Lower Extremity Fugl-Meyer scores (higher
scores represent improved sensorimotor recovery). C. Berg
Balance Scale (higher scores represent improved balance). D.
Six minute walk test (distance covered). Significant
difference within Lokomat group between pre- and post-test
(p < 0.05). t Significant difference within manual group
between pre- and post-test (p < 0.05).

performance of certain functional tasks including: dres-
sing, walking a mile, and climbing stairs, p = 0.004, with
an effect size of 0.47.

In an effort to differentiate changes in motor control
from aerobic conditioning effects, we conducted two
post-hoc correlations: 1) self-selected overground walk-
ing speed and 6-minute walk test, and 2) Berg Balance
Scale and 6-minute walk test. Due to the influence of gait
speed and balance in a chronic population (mean 5.5
years post-stroke), previous work has cautioned against
interpreting the 6-minute walk test as an indicator of
aerobic capacity [38]. However, in our study of
participants who averaged 3.3 years post-stroke, no
significant relationship was identified between either
changes in 6-minute walk test and self selected gait
speed, r= 0.14, p = 0.61, or changes in 6-minute walk test
and balance (Berg Balance Scale), r = 0.27, p = 0.32.
Therefore, improvements in gait speed and balance
detected in the present study could be attributed to
enhanced locomotor control and were not likely due to
changes in endurance as measured using the 6-minute
walk test.

Our second aim was to assess locomotor-training effects
at faster vs. slower treadmill speeds. As anticipated,
independent of whether training occurred in the

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

Lokomat or manual-BWSTT mode, average weekly
training speeds within the fast and slow groups were
similar, p > 0.29 (Table 3). Therefore, data from both
Lokomat and manual groups were collapsed to isolate
the effects of training speed. On average, participants in
the fast group trained at speeds that were 50% above
their baseline overground walking speed, while the
training speed in the slow group was similar to their
baseline overground walking speed. Despite these
differences in absolute and relative between-group
training speeds, no group differences were noted on
primary or secondary outcome measures, p > 0.28.

The primary purpose of this pilot study was to compare
the efficacy of locomotor training implemented using a
Lokomat robotic gait orthosis versus manual-BWSTT in a
sample with chronic locomotor deficits post-stroke. In
conducting this study, we sought to determine the key
parameters and reveal challenges in future randomized
controlled trials with larger cohorts.

Although statistically significant differences were not
apparent between Lokomat and manual groups in this
small, pilot trial, our data revealed significantly greater
training-related improvements within the Lokomat, but
not the manual group. Differential treatment effects
produced include: 1) Lokomat group improvements in:
self-selected overground walking speed, gait symmetry
(SLRabs), fast overground walking speed, lower extremity
motor impairment (Fugl-Meyer), function (short

physical performance battery), and balance (Berg Bal-
ance Scale), and 2) manual group improvements solely
in balance outcomes (Berg Balance Scale).

Changes in self-selected walking speed
Modest improvements in self-selected overground walk-
ing speed were not unexpected considering that partici-
pants were in the chronic post-stroke phase in which
recovery is expected to be minimal. The minimal
detectable change (MDC) necessary to conclude clini-
cally significant change in gait speed has occurred ranges
from 0.07-0.36 m/s in a post-stroke population [39].
Therefore, the 0.1 m/s increase from the mean baseline
value revealed in the Lokomat group was not only
statistically significant, but also clinically important with
an effect size of 0.32. This modest, but significant, effect
is especially notable considering the small treatment
dose in this preliminary work. Despite the statistically
non-significant between-group difference, it is also
notable that participants in the Lokomat group increased
overground gait speed by 16% over baseline, whereas
those in the manual group advanced by only 4.8%. The
magnitude of this difference suggests a potential clinical
advantage of Lokomat training.

While the overall outcome of this pilot study provides
further evidence for the efficacy of locomotor training,
the lack of statistical evidence supporting superiority of
either Lokomat or manual form of locomotor training
highlights inconsistencies between previous studies. Our
results agree with investigations during the acute and

Table 3: Treadmill training speeds and self-selected walking speeds of fast and slow training groups

Group Initial Treadmill training speed (m/s) Final overground
overground SSWS (m/s)
SSWS (m/s)
Week I Week 2 Week 3 Week 4 Mean

Fast 0.6 0.2 0.8 0.1 0.9 0.1 0.94 0.0 1.0 0.1 0.9 0.2 0.7 0.4
(0.2-1.0) (0.5-I.1) (0.7-1.2) (0.7-1.2) (0.8-1.3) (0.7-1.2) (0.3-1.4)
Robot 0.6 0.3 0.9 0.1 1.0 0.1 1.0 0.1 1.1 0.2 1.0 0.1 0.7 0.5
(0.3-1.0) (0.8-1.1) (0.9-1.2) (0.9-1.2) (0.9-1.3) (0.9 1.2) (0.4-1.4)
Manual 0.6 0.3 0.7 0.2 0.8 0.1 0.9 0.11 1.0 0.1 0.8 0.1 0.7 0.3
(0.2-0.9) (0.5-0.8 (0.7-0.9) (0.7-1.0) (0.8-. 1) (0.7 0.9) (0.3-0.9)
Slow 0.6 0.3 0.5 0.1 0.6 0.1 0.6 0.1 0.6 0.1 0.6 0.1 0.7 0.3
(0.3-0.9) (0.3-0.7) (0.3-0.7) (0.3-0.7) (0.4-0.7) (0.3-0.7) (0.3-1.0)
Robot 0.7 0.3 0.6 0.1 0.7 0.1 0.7 0.0 0.7 0.0 0.7 0.0 0.8 0.3
(0.3-0.9) (0.6-0.7) (0.6-0.7) (0.6-0.7) (0.7-0.7) (0.7 0.7) (0.3- .0)
Manual 0.6 0.3 0.5 0.1 0.5 0.1 0.5 0.2 0.6 0.1 0.5 0.1 0.7 0.4
(0.3-0.9) (0.3-0.6) (0.3-0.6) (0.3-0.7) (0.4-0.7) (0.3 0.6) (0.3-1.0)

Note: values are mean SD (range).
Abbreviations: SSWS = self selected walking speed.

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

subacute post-stroke stages using the Lokomat [18] and a
robotic gait trainer [17] in which differences were noted
within groups, but no differences were identified in the
extent of improvement between robot and manual
groups. However, in their recent publication, Hornby
et al. [20] studied a sample of hemiparetic individuals of
greater chronicity (i.e. 4-6 yrs post-stoke) and with
lower baseline function (i.e. 0.4 m/s preferred gait
speed) than our participant pool and reported greater
increases in overground gait speed in a manual-BWSTT
group compared with a Lokomat trained group. While
speculative at this point, a secondary reduction in
cardiorespiratory capacity of chronic stroke survivors
[38] suggests that participants with long-term functional
deficits may benefit from the aerobic training induced by
the higher metabolic cost required for manual-BWSTT
[40]. Results of the 6-minute walk test highlight this
potential effect. A statistically significant improvement
of 34 m, indicative of an aerobic conditioning effect, was
found in the manually-trained group of Hornby et al.,
while a statistically non-significant reduction of 24 m
was found in our manually-trained group. Further, a lack
of correlation between change scores on the 6 minute
walk test and self-selected walking speed suggests that
increases in gait speed revealed in the present study are
more likely to have resulted from factors other than
increased physical capacity, including enhanced neural
control, and reflect a change in the underlying locomo-
tor pattern. Moreover, our decision to remove the AFO
from all participants during locomotor training appears
to have proven effective in improving gait symmetry. In
contrast, Hornby and co-workers elected not to focus on
improving kinematics, performed locomotor training
with AFOs in place, and failed to detect changes in gait
symmetry. Future investigations comparing Lokomat
versus manual training with a common goal of improved
kinematics at different stages of chronicity, may provide
more definitive insight into an approximate timeline of
beneficial use of one approach over the other.

Changes in gait symmetry
Our intent throughout locomotor training, whether
delivered using the Lokomat or manually, was to
normalize gait kinematics during stepping, while simul-
taneously controlling for variables of BWS and stiffness
and treadmill speed. Consistency of training variables in
both groups enabled us to discern important differences
between motor learning induced by Lokomat and
manual-BWSTT. Kinematic improvements in paretic
step length symmetry were noted only in the Lokomat
group, suggesting greater benefits of consistent, normal-
ized kinesthetic input delivered automatically at a
constant guidance force to both lower extremities during
gait. In contrast, the inconsistency in both kinematic

stepping patterns and manual cues to the hemiparetic leg
with therapist-determined level of assistance appears to
be a limitation to improvements in gait symmetry,
thereby supporting previous research [20].

Further improvements in gait symmetry within the
Lokomat group may have arisen from the safe removal
of the foot straps in 3 participants. Foot straps are
included as part of the standard Lokomat package and
are meant to passively set the ankle in neutral and enable
foot clearance. Generation of paretic leg propulsive
forces is correlated with gait speed, effective step length
symmetry [26] and plantarflexion activity during late
stance [41]. For these reasons, we strongly encouraged
active plantarflexion/push-off and provided verbal and
tactile cues in an effort to induce motor learning and
voluntary execution of plantarflexion. Examining indi-
vidual subject changes in gait speed and symmetry, we
noted that two of the three participants who were able to
train without foot straps demonstrated the most
remarkable improvements in step length symmetry.
Though we searched for other commonalities between
these participants, including sensorimotor impairment
scores, initial functional level, location and type of
lesion, time since stroke, and age, the one similarity was
the removal of the foot strap during training. From a
biomechanical perspective, the automated symmetrical
step length of the Lokomat would have forced the
propulsive forces of the ankle plantarflexors to be
initiated posterior to the subject's center of mass
(COM) at pressing. A strong relationship between step
length symmetry and propulsive force symmetry in
addition to the importance of the plantarflexors to
propulsive force supports this premise [26,42]. However,
further investigations conducted without the use of the
foot straps in a larger cohort are necessary to address this
issue definitively. At this point we are only able to
speculate that a more significant training effect was
induced by the opportunity to experience active ankle
movement and a normal range of ankle motion while in
the Lokomat.

Changes in balance
Results also revealed significantly improved balance
scores producing small to moderate effect sizes on the
BBS in both groups. Scores fell within the range in which
each 1-pt increase translates to a 6-8% decrease in fall
risk. Therefore, the 1.4-pt improvement following
Lokomat training and the 4-pt improvement following
manual training equates to an 8-14% and 24-32%
reduction in fall risk, respectively [43]. These results are
not surprising given that treadmill training with or
without the Lokomat exposes the central nervous system
to several sources of conflicting sensory information,

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

thereby constantly challenging sensory re-weighting
processes. Throughout training, proprioceptive inputs
from the lower extremity mimic an appropriate stepping
pattern on a moving support surface while vestibular and
visual cues remain relatively stable. Sensory integration
training in such challenging situations may have also
translated to improved balance scores in our subject
sample. Moreover, the importance of active lateral
stabilization to the control of static and dynamic posture
and prevention of falls is well established. In this respect,
the manual group had a particular advantage in inducing
balance improvements with increased lateral freedom
compared to the constraints imposed by the Lokomat.

Comparison of gait training speeds
The second purpose of this study was to assess effects of
training at speeds comparable to preferred walking
speeds of non-disabled individuals versus speeds com-
parable to persons post-stroke. Against our hypothesis,
our data revealed no differences attributable to training
speed on primary or secondary variables. Our hypothesis
was based, in part, on a related study by Sullivan et al.
[8], who found that training at speeds approaching
normal walking speed (0.89 m/s) improved preferred
overground gait speed compared with a considerably
slower training speed (0.22 m/s). It is possible that since
the mean training speed in our slow group at 0.58 m/s
was higher, yet more functional, than the slow group in
Sullivan et al., the difference between fast and slow
groups was not sufficient to reveal training-related
differences. Nevertheless, the slow speed in the current
study was representative of the pre-intervention comfor-
table over ground walking speed of the participants,
while the fast speed corresponded to a normal (e.g. non-
disabled) gait speed of 1.3 m/s [44]. In this view, the two
studies are complementary with results supporting
training at or above participants' comfortable over
ground walking speed rather than non-functional speeds
that are below mean overground gait speed of indivi-
duals with stroke.

Study limitations and implications
It may be argued that the automaticity of the Lokomat
may have afforded the opportunity to take more steps
and, in turn, receive quantitatively more gait training.
However, since the mean training speed did not differ
between groups, the difference in the number of steps
taken would likely be minimal. Moreover, our goal was
to evaluate the effectiveness of the Lokomat compared to
manual training within a 30 min time frame typically
allotted in clinical settings.

As with most pilot studies, the small sample size and
resultant low statistical power limit interpretation of this

study. However, given that participants demonstrated
significant improvements after only 12 treatment ses-
sions in the chronic post-stroke stage, the small to
moderate effect sizes are promising. Our results support
the original intent of the present pilot study, which was
to determine if a larger clinical trial was plausible and
should be conducted. This study was different from
previous studies because we controlled for many factors
such as handrail use, orthotic use, the amount of body
weight support, and we placed emphasis on normalizing
kinematics during training in order to isolate the specific
effects of automated vs. manually-assisted treadmill
training. Thus, we were able to show that subjects
benefited from training with the Lokomat for a number
of performance metrics. One product of our pilot study
is tangible results from which to project requisite sample
size(s) for future randomized controlled trials designed
to definitively evaluate the efficacy of Lokomat com-
pared to manual training. Our primary outcome, self-
selected overground walking speed, revealed a between
group effect size of 0.59 favoring Lokomat vs. manual
training with a probability of 0.6. From this we
determined that 51 subjects per group are necessary to
detect significant between-group differences. For paretic
step length ratio, the demonstrated between-group effect
size was 0.73 favoring Lokomat vs. manual training with
a probability of 0.70 which translates to a projected
sample size of 34 subjects per group. Finally, for fast
walking speed, our data revealed a between-group effect
size of 0.70 favoring Lokomat vs. manual training at a
probability of 0.69 which projects to a sample size of 37
subjects per group to detect between group differences.
All sample sizes were projected assuming 80% power at a
5% level of significance.

While these early, positive findings are encouraging,
taken together with the disparate findings reported in the
current literature [18-20,45,46], there is a clear need to
pursue both the questions regarding efficacy of locomo-
tor training, in general, and robotic-driven locomotor
training specifically. We recommend a follow-up study
based on our sample size calculations to: probe whether
these findings will be reproduced in a larger sample,
determine additional differential effects that may not
have been revealed in this short pilot trial and test for
retention of training effects over an extended period of
weeks to months post-training. Further, the advantages
and disadvantages of each approach to locomotor
training should be weighed in terms of cost-effectiveness,
ease of application, and consistency of treatment before
definitive conclusions regarding Lokomat use in stroke
rehabilitation settings may be drawn. Early evidence
favoring locomotor training [9] as an effective

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Journal of NeuroEngineering and Rehabilitation 2009, 6:18

intervention post-stroke is tempered by the personnel
costs involved (2-4 therapists/trainers), which are
unrealistic for the majority of clinical settings. Indeed,
many clinics and laboratories that deliver locomotor
training depend on considerable volunteer and/or
student manpower to simply conduct locomotor train-
ing [47] let alone achieve financial feasibility [48].
Equally important is the considerable risk of injury to
the trainers representing a significant liability for health
care administrators. In this light, equivalent functional
outcomes achieved between Lokomat and manual
locomotor training represent an favorable result in
which Lokomat training may be used in place of manual
training to benefit a larger proportion of affected
individuals. Further, as demonstrated in the present
study, when administered carefully and systematically,
robotic-driven motor learning appears to promote
adaptation at the level of the locomotor pattern rather
than simply offering aerobic conditioning or non-
specific changes that contribute to increased gait speed.
Long-term retention of these locomotor adaptations is
desired and the target of future investigation beyond this
initial pilot study. Further research is required to identify
the ideal population (i.e. hemiparetic chronicity, sever-
ity) for locomotor training, especially robotic-driven
approaches to locomotor training, and to elaborate the
critical parameters of effective locomotor training,
including the ideal amount of variability in kinematic
guidance and the most effective schedule for adjusting
and ultimately withdrawing kinematic guidance.

While this pilot study revealed no between-group
differences in efficacy of Lokomat versus manual
locomotor training, significant within-group effects
reveal positive effects of locomotor training and suggest
that Lokomat training may offer a potential advantage of
this mode over manual BWSTT. A modest dose of
Lokomat training is effective for improving overground
walking speed and gait symmetry, and other lower
extremity impairments and physical function in persons
with chronic hemiparesis post-stroke. Consequently,
larger, randomized controlled trials are warranted.

Competing interests
The authors declare that they have no competing

Authors' contributions
KPW assisted in experimental design, conducted the
experiments and data collection, analyzed the data, and
was responsible for the initial drafting of the manuscript.
CP conceived the study and experimental design, assisted
with the experiments and data collection, and helped

draft the manuscript. Both authors read and approved
the final manuscript.

We thank George Chen, Ph.D. and Jeff Jarmillo, PT, M.S. for assistance in
collecting experimental data, Fayaza Mullamithawala, PT and Jeff Jarmillo,
PT, M.S., for assistance with the locomotor intervention, and Fadi Tayim
for coordinating participant logistics. Dr. Sam Wu of the University of
Florida Department of Biostatistics and the VA Brain Rehabilitation
Research Center provided statistical consultation and advice.

This study was conducted at the Rehabilitation Research and Development
Center, VA Palo Alto Health Care System, Palo Alto, CA and funded by
VA RR&D Project no. B540231 (Principal Investigator, Patten). Dr.
Westlake is supported by a Clinical Research Initiative Fellowship through
the Canadian Institutes of Health Research.

A portion of this work was presented at the Society for Neuroscience
Annual Meeting, November, 2008, Washington, DC.

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