Kinematics and muscle activity of individuals with incomplete spinal cord injury during treadmill stepping with and without manual assistance.

Abstract

Treadmill training with bodyweight support and manual assistance improves walking ability of patients with neurological injury. The purpose of this study was to determine how manual assistance changes muscle activation and kinematic patterns during treadmill training in individuals with incomplete spinal cord injury.
We tested six volunteers with incomplete spinal cord injury and six volunteers with intact nervous systems. Subjects with spinal cord injury walked on a treadmill at six speeds (0.18-1.07 m/s) with body weight support with and without manual assistance. Healthy subjects walked at the same speeds only with body weight support. We measured electromyographic (EMG) and kinematics in the lower extremities and calculated EMG root mean square (RMS) amplitudes and joint excursions. We performed cross-correlation analyses to compare EMG and kinematic profiles.
Normalized muscle activation amplitudes and profiles in subjects with spinal cord injury were similar for stepping with and without manual assistance (ANOVA, p > 0.05). Muscle activation amplitudes increased with increasing speed (ANOVA, p < 0.05). When comparing spinal cord injury subject EMG data to control subject EMG data, neither the condition with manual assistance nor the condition without manual assistance showed a greater similarity to the control subject data, except for vastus lateralis. The shape and timing of EMG patterns in subjects with spinal cord injury became less similar to controls at faster speeds, especially when walking without manual assistance (ANOVA, p < 0.05). There were no consistent changes in kinematic profiles across spinal cord injury subjects when they were given manual assistance. Knee joint excursion was approximately 5 degrees greater with manual assistance during swing (ANOVA, p < 0.05). Hip and ankle joint excursions were both approximately 3 degrees lower with manual assistance during stance (ANOVA, p < 0.05).
Providing manual assistance does not lower EMG amplitudes or alter muscle activation profiles in relatively higher functioning spinal cord injury subjects. One advantage of manual assistance is that it allows spinal cord injury subjects to walk at faster speeds than they could without assistance. Concerns that manual assistance will promote passivity in subjects are unsupported by our findings.

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BioMed Central
Page 1 of 14
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Journal of NeuroEngineering and
Rehabilitation
Open Access
Research
Kinematics and muscle activity of individuals with incomplete spinal
cord injury during treadmill stepping with and without manual
assistance
Antoinette Domingo*1, Gregory S Sawicki1,2 and Daniel P Ferris1,3,4
Address: 1Division of Kinesiology, University of Michigan, Ann Arbor, MI, USA, 2Department of Mechanical Engineering, University of Michigan,
Ann Arbor, MI, USA, 3Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA and 4Department of Physical Medicine
and Rehabilitation, University of Michigan, Ann Arbor, MI, USA
Email: Antoinette Domingo* - adomingo@umich.edu; Gregory S Sawicki - gsawicki@umich.edu; Daniel P Ferris - ferrisdp@umich.edu
* Corresponding author
Abstract
Background: Treadmill training with bodyweight support and manual assistance improves walking ability
of patients with neurological injury. The purpose of this study was to determine how manual assistance
changes muscle activation and kinematic patterns during treadmill training in individuals with incomplete
spinal cord injury.
Methods: We tested six volunteers with incomplete spinal cord injury and six volunteers with intact
nervous systems. Subjects with spinal cord injury walked on a treadmill at six speeds (0.18–1.07 m/s) with
body weight support with and without manual assistance. Healthy subjects walked at the same speeds only
with body weight support. We measured electromyographic (EMG) and kinematics in the lower
extremities and calculated EMG root mean square (RMS) amplitudes and joint excursions. We performed
cross-correlation analyses to compare EMG and kinematic profiles.
Results: Normalized muscle activation amplitudes and profiles in subjects with spinal cord injury were
similar for stepping with and without manual assistance (ANOVA, p > 0.05). Muscle activation amplitudes
increased with increasing speed (ANOVA, p < 0.05). When comparing spinal cord injury subject EMG data
to control subject EMG data, neither the condition with manual assistance nor the condition without
manual assistance showed a greater similarity to the control subject data, except for vastus lateralis. The
shape and timing of EMG patterns in subjects with spinal cord injury became less similar to controls at
faster speeds, especially when walking without manual assistance (ANOVA, p < 0.05). There were no
consistent changes in kinematic profiles across spinal cord injury subjects when they were given manual
assistance. Knee joint excursion was ~5 degrees greater with manual assistance during swing (ANOVA, p
< 0.05). Hip and ankle joint excursions were both ~3 degrees lower with manual assistance during stance
(ANOVA, p < 0.05).
Conclusion: Providing manual assistance does not lower EMG amplitudes or alter muscle activation
profiles in relatively higher functioning spinal cord injury subjects. One advantage of manual assistance is
that it allows spinal cord injury subjects to walk at faster speeds than they could without assistance.
Concerns that manual assistance will promote passivity in subjects are unsupported by our findings.
Published: 21 August 2007
Journal of NeuroEngineering and Rehabilitation 2007, 4:32doi:10.1186/1743-0003-4-32
Received: 27 September 2006
Accepted: 21 August 2007
This article is available from: http://www.jneuroengrehab.com/content/4/1/32
© 2007 Domingo et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Background
Several investigators have shown that body weight sup-
ported treadmill training can improve walking ability in
those with incomplete spinal cord injury [see Additional
file 1] [1-8]. During this treatment, the patient is sus-
pended in a standing position above a treadmill by means
of a modified parachute harness so that the patient only
bears a portion of his weight on their legs. A therapist on
each side of the person then manually assists his legs
through walking motions while the treadmill belt is mov-
ing. A third therapist may also stand behind the patient to
help stabilize the trunk. One study showed that 80% of
people with incomplete spinal cord injury who used a
wheelchair for mobility became functional ambulators
after body weight supported treadmill training [3]. The
effects of this training were maintained long after the
intensive treadmill training ended. However, Dobkin et
al. performed a multi-center randomized clinical trial that
had more equivocal results [7]. They found that body
weight supported treadmill training was no more effective
than highly intensive "conventional" physical therapy in
improving walking ability. Clearly more research is
needed to examine mechanisms and ideal training param-
eters for body weight supported treadmill training.
Recently, Hidler highlighted the need for more evidence
supporting the choice of specific training parameters [9].
The amount of body weight support and the walking
speed are just a few of the parameters that can greatly vary
during treatment. We do not know what is the most effec-
tive and efficient manner to set these parameters or how
to progress them as a patient makes functional gains.
Another factor of training to consider is the use of func-
tional electrical stimulation with locomotor training. Sev-
eral studies have found therapeutic effects of functional
electrical stimulation during gait rehabilitation [10-12],
but like body weight support and walking speed, it is not
clear how to optimize its use.
Another parameter of body weight supported treadmill
training that needs to be considered is the amount of
mechanical assistance that should be given and the man-
ner in which it is given. One approach is to allow patients
to practice stepping on a treadmill with body weight sup-
port but no mechanical assistance at all. This could only
be done for patients with sufficient motor ability so that
body weight support alone facilitated stepping. When this
is not possible, the most readily available and most used
form of assistance is manual. Unfortunately, this is also
very labor intensive and requires a high level of skill to
administer. The assistance given could vary from step to
step and/or from trainer to trainer. To address these limi-
tations, several groups have developed robotic devices to
provide mechanical assistance during stepping [13-17].
One possible downside to manual or robotic assistance
during body weight supported treadmill training is dimin-
ished motor learning. Physical guidance improves per-
formance during the learning phase of an upper limb task
while guidance is given, but the improvement in perform-
ance is not retained once the guidance is removed [18-20].
There is no clear evidence on how guidance affects learn-
ing in cyclical lower limb tasks. A fundamental assump-
tion of body weight supported treadmill training is that it
promotes activity dependent plasticity to improve func-
tion ability. Activity dependent plasticity depends on suf-
ficient and appropriate voluntary drive to promote
modifications in synaptic connections [21,22]. If manual
assistance promotes passivity, then it may be detrimental
because diminished neural activation limits the possibil-
ity of neural plasticity in relevant circuits.
In contrast, physical guidance may be necessary to learn
how to perform a walking movement correctly. Presuma-
bly, manual assistance during body weight supported
treadmill training helps to ensure that the patient is expe-
riencing the correct kinematics of walking. This could be
important because sensory information is an input to the
locomotor neural networks. Afferent feedback directly
influences the spinal generation of muscle activity that
produces human walking [23-28]. Therefore, manual
assistance could result in afferent feedback more typical of
non-disabled persons during stepping practice. In addi-
tion, there are some situations in which learning a move-
ment without physical guidance could be dangerous.
When learning to walk after spinal cord injury, manual
assistance certainly increases safety, especially when walk-
ing at faster speeds.
The purpose of this study was to determine how manual
assistance affects lower limb electromyographic (EMG)
activity and joint kinematics in subjects with incomplete
spinal cord injury during body weight supported tread-
mill training. There are two competing hypotheses on
how EMG activity might be affected by treadmill training
with manual assistance. One possibility is that manual
assistance decreases the patient's effort, thereby reducing
EMG amplitudes. An alternative possibility is that manual
assistance provides more normative kinematic patterns,
resulting in more appropriate sensory feedback and
increasing EMG amplitudes. We examined individuals
with incomplete spinal cord injury that were able to walk
with and without manual assistance at multiple speeds
during body weight supported treadmill training to com-
pare kinematics and muscle activation. The findings of
this study should help to determine if manual assistance
affects EMG activity and joint excursions for body weight
supported treadmill training.

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Methods
Subjects
We tested six adult volunteers with an incomplete spinal
cord injury and six neurologically intact adult volunteers.
Six subjects with incomplete spinal cord injury (ASIA
Impairment Scale Classification of C or D) at the cervical
or thoracic level participated in the study. Subjects were at
least 12 months post-injury and free of any conditions
that would limit their ability to safely complete testing.
Five of six subjects were community ambulators with pre-
ferred over ground walking speeds of 0.37–0.95 m/s. Of
these five subjects, four used canes. Table 1 details the
cause, classification, level of spinal injury, preferred walk-
ing speed, and assistive devices of each subject. Six control
subjects (age = 25.8 ± 2.9 years, mass = 66.7 ± 13.4 kg,
mean ± SD) without neurological injury also participated
in the study. The University of Michigan Institutional
Review Board approved this project and all subjects gave
informed consent prior to participating.
Procedures
Subjects with spinal cord injury walked on a treadmill
with and without manual assistance at six different speeds
(0.18, 0.36, 0.54, 0.72, 0.89, 1.07 m/s) with body weight
support (Robomedica, Inc., Irvine, CA). Additional video
files show procedures at one speed for one subject [see
Additional files 1 &2]. All subjects with spinal cord injury
underwent one to two training sessions on the treadmill
with body weight support prior to data collection to
familiarize them with the procedure. The amount of body
weight support and stepping speeds achieved varied
between subjects due to their different walking abilities.
Subjects with spinal cord injury were supported with 30%
body weight support unless they required greater support
to walk at multiple treadmill speeds. Initially, subjects
were asked to walk with 30% body weight support with-
out manual assistance. If they were unable to take steps at
this level of support at 0.36 m/s, body weight support was
increased in 10% increments until the subject could walk
safely at this speed without manual assistance. Three sub-
jects walked with 30% body weight support, two subjects
walked with 50% body weight support, and one subject
Table 1: Subject Information. Data for each subject showing age, body size, injury level, walking ability, body weight support level and
walking speeds completed during the study.
SubjectAge (yrs.) Sex
Height
(cm)
Weight
(kg)
Injury
Etiology
Injury
Level
ASIA*
Level
Post Injury
(mos.)
Walking
Aids
Overground
Walking
Speed (m/s)
BWS Level
(%)
Speeds w/o
MA (m/s)
Speeds w/
MA (m/s)
A 54F DermoidT11/T12C64Cane (L,
R)
Ankle-foot
orthosis
(L)
Quad
Cane (R)
0.4130%
165.1 cm
73.7 kg
Tumor 0.18–0.89
0.18–0.89
B 52F Myxopapilla
ry
Ependymom
a
T8/L2D93 0.6130%
156.20.18–0.36
58.1 kg
F
175.3 cm
115.3 kg
0.18–0.72
50%
0.18–1.07
0.18–1.07
C 38Transverse
Myelitis
T5D 77Cane (R)
Ankle-foot
orthosis
(L)
-
0.37
D 24M TraumaT10/T11D 1110.95 30%
185.4 cm
101.5 kg
M
171.5 cm
83.0 kg
M
0.18–1.07
0.18–1.07
60%
0.18–0.54
0.18–0.89
50%
E 55 SarcoidosisC5/C6C 144Cane (R)0.48
F50 TraumaC4/C5C 83Wheelchai
r
Soft ankle
brace (L,
R)
-
193.0 cm
95.3 kg
0.18–0.72
0.18–1.07
* ASIA = American Spinal Injury Association Impairment Scale. A = Complete, E = Normal.

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walked with 60% body weight support. The goal of the
manual assistance was to minimize gait deviations (e.g.,
increasing step length, increasing toe clearance and hip
flexion during swing). We attempted to collect data at all
speeds for all subjects but only two subjects were able to
walk at all six speeds with and without assistance. We col-
lected data on the remaining subjects from the trials they
were able to safely complete. Table 1 shows the stepping
speeds each subject was able to achieve. Subjects who nor-
mally used lower limb orthoses wore them during testing
to ensure their safety (Table 1). Control subjects walked
on the treadmill without manual assistance at all speeds
with 30% body weight support to match the baseline con-
dition of the subjects with spinal cord injury.
The same trainers manually assisted all subjects following
the procedures described by Behrman and Harkema for
locomotor training with partial body weight support [6].
The trainers were instructed and supervised by a former
trainer who was from the UCLA Human Locomotion
Research Center that directed a large scale clinical trial on
body weight supported treadmill training [29].
Data acquisition and analysis
While walking under the two experimental conditions, we
collected surface electromyographic and kinematic data.
We used a Konigsberg Instruments, Inc. (Pasadena, CA)
telemetry EMG system to record activity from eight mus-
cles on one lower limb (tibialis anterior, TA; soleus, SO;
medial gastrocnemius, MG; lateral gastrocnemius, LG;
vastus lateralis, VL; vastus medialis, VM; rectus femoris,
RF; and medial hamstring, MH). Inter-electrode distance
was 2.5 cm for all subjects and muscles. Electrodes were
circular with a diameter of 1.1 cm. We verified that cross-
talk was negligible by visual inspection of the EMG sig-
nals[30]. We also used footswitches to delineate the
stance phase and swing phase of gait. We placed electro-
goniometers (Biometrics, Ltd., Ladysmith, VA) at the
ankle, knee and hip joints on each leg to record joint
angles. If the patient wore an ankle foot orthosis, the goni-
ometer was placed on the outside of the orthosis. The
computer collected all analog data at 1200 Hz for 15–25
seconds per trial depending on speed (Motion Analysis
Corporation, Santa Rosa, CA). Subjects also wore foots-
witches as insoles to indicate the time each foot was or
was not on the ground (B & L Engineering, Tustin, CA).
Contacts in the footswitches were at the heel, fifth meta-
tarsal, first metatarsal, and great toe to signify when those
areas of the foot bearing weight. Subjects with spinal cord
injury performed two trials of each condition (with and
without manual assistance) and speed in a randomized
order. Between 4 and 19 steps were analyzed per trial
depending on speed. The difference in number of steps
analyzed across trials and subjects was not likely to artifi-
cially alter the results [31]. Although some subjects could
walk at faster speeds with manual assistance than they
could without, only trials from speeds at which the subject
could walk both with and without manual assistance were
included. We only analyzed EMG and kinematic data
from speeds that subjects could both walk with and with-
out assistance because EMG amplitudes are a function of
walking speed and including the data from the higher
walking speeds would skew the results.
We used commercial software (Visual 3D, C-Motion, Inc.,
Rockville, MD) to process collected EMG and kinematic
data. EMG data were high-pass filtered (20 Hz) to remove
artifacts while preserving the integrity of the data, and
then rectified and low-pass filtered (25 Hz). Kinematic
data were low pass filtered at 6 Hz [32]. Averaged EMG
and kinematic profiles were time normalized to the per-
centage of the stride cycle, beginning and ending with heel
strike of the same foot. We calculated the EMG root-
mean-square (RMS) for each step cycle within a trial for
each muscle, and then averaged these values for an overall
RMS value for each trial. We also calculated separate RMS
values for the stance and swing phases of gait.
For each muscle, we normalized EMG RMS data to the
highest average RMS that occurred in that muscle without
manual assistance during one of the two trials at 0.36 m/
s. We chose this speed for normalization because it was
the highest speed that all subjects with spinal cord injury
could achieve. Using JMP statistical software (Cary, NC),
we used a repeated measure ANOVA (individual subject
by speed by condition) to test for significant differences
between normalized RMS values for the stance and swing
phases separately. We also used a repeated measure
ANOVA (individual subject by speed by condition) to test
for significant differences between joint range of motion
values. Tukey HSD post-hoc tests were performed to iden-
tify differences between specific groups. For power analy-
ses, we calculated the least significant values, which gave
the sensitivity of the test. We then compared the least sig-
nificant values to the actual differences in group means to
determine if testing any more subjects would likely
change our results.
We performed cross-correlation analyses using Equation
(1) to compare averaged electromyographic waveforms
and kinematic profiles of control subjects with the profiles
of each spinal cord injury subject with and without man-
ual assistance [33-35].
where xi and yi are two series of data, and i = 0, 1, 2, ..., N-
1. The first series of data was the averaged control subject
R
x y
i i
(
xy
ii
=
())
Σ
/
ΣΣ
21 221 2
/
,

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data, and the second series was the data from individual
subjects with spinal cord injury. Because the data were
normalized to the percentage of the gait cycle, N = 101 in
all analyses. We used the cross-correlation results to assess
if manual assistance altered the shape and timing of mus-
cle activation and kinematic profiles of subjects with spi-
nal cord injury so that it was more similar to control
subject profiles. We also performed cross-correlation anal-
yses to compare EMG waveforms and kinematic profiles
of subjects with spinal cord injury walking with manual
assistance to walking without manual assistance. We per-
formed repeated measure ANOVAs (individual subject by
speed by condition) to test for significant differences in R-
values and time lags. Tukey HSD post-hoc tests were per-
formed to identify specific differences between groups.
Power analyses were also carried out where appropriate.
We calculated coefficients of variation (CV) of EMG acti-
vation and joint angle profiles using Equation (2) to
quantify variability of the different conditions [36].
where N is the number of intervals over the stride, Xi is the
mean value of the variable at the ith interval, and σi is the
standard deviation of variable X about Xi. We performed a
repeated measure ANOVA (individual subject by speed by
condition) to test for significant differences in the coeffi-
cients of variation of the joint angle profiles. We per-
formed post-hoc tests and power analyses as described
above.
Results
Three of six subjects with spinal cord injury could walk at
faster speeds with manual assistance than without. The
average highest walking speed without manual assistance
was 0.76 m/s. The average walking highest speed with
manual assistance was 0.95 m/s (Table 1).
Electromyography
There were clear differences between muscle activation
patterns in subjects with spinal cord injury and control
subjects. However, muscle activation profiles in subjects
with spinal cord injury walking with manual assistance
were very similar to profiles while walking without man-
ual assistance (Figures 1, 2, and 3). Cross-correlation anal-
yses of average EMG waveforms between with and
without manual assistance produced correlation values
greater than 0.89 and phase lags less than 2% (Table 2).
When comparing spinal cord injury data to control data,
neither the condition with manual assistance nor the con-
dition without manual assistance showed a greater simi-
larity to the control subject data (correlation and phase
lag, ANOVA, p > 0.05). The exception was that when the
subjects with SCI were given manual assistance, the pro-
file of the vastus lateralis activation was more similar to
the profile of the control subjects (p = 0.002, R = 0.91
without manual assistance, R = 0.93 with manual assist-
ance). Power analyses showed that the differences in
means of the R-values for TA, SO, LG, VM, and VL EMG
profiles and the time shift for SO EMG profile were greater
than the calculated least significant values. Therefore, this
indicates that there is a 95% chance that there actually is
no difference in R-values or time shift between the two
conditions in these muscles [37].
Muscle activation amplitudes in subjects with spinal cord
injury walking with manual assistance were very similar to
amplitudes during walking without manual assistance
(Figures 4 and 5). There were no significant differences in
normalized EMG RMS between the two conditions for
any muscles (ANOVA, p > 0.05), except VM during stance
(ANOVA, p = 0.02). Power analyses comparing the differ-
ences in means and the least significant values showed
that there was a 95% chance that there was no difference
in EMG RMS between the two conditions in the SO and
VL during the stance phase and MH during the swing
phase.
There were increases in muscle activation amplitudes of
subjects with spinal cord injury with speed. Stance EMG
RMS increased from slowest to fastest speeds for all exper-
imental conditions in soleus (96%), medial gastrocne-
mius (120%), vastus lateralis (44%), rectus femoris
(48%), and vastus medialis (61%) (all p < 0.01) (Figure
4). Swing EMG RMS increased in soleus (61%), medial
gastrocnemius (33%), vastus medialis (61%), and vastus
lateralis (49%) (all p < 0.04) (Figure 5). The remaining
muscles did not have significant increases in EMG RMS (p
> 0.05).
The shape of muscle activation patterns in subjects with
spinal cord injury tended to become less similar to con-
trols at faster speeds, especially when walking without
manual assistance. When comparing the without manual
assistance condition to controls, R-values became signifi-
cantly less from the slowest to the fastest speed in TA (0.85
to 0.83), SO (0.87 to 0.80), MG (0.84 to 0.74), LG (0.85
to 0.74), VM (0.94 to 0.90), and VL (0.94 to 0.90)
(ANOVA, p < 0.05). The phase shift also became larger
with increasing speed in LG (5 to -26) (p < 0.05). When
comparing the manual assistance condition to controls,
only the TA had a significantly lower R-value with increas-
ing speed (0.87 to 0.83) (ANOVA, p < 0.05).
CV
N
N
X
i
i
N
∑
i
i
N
∑
=
=
=
1
1
2
1
1
σ
,