Changes in Muscle Co-activation in Spinal Cord Injured Individuals After Body-Weight Supported
Treadmill Training
1
Sabrina S.M. Lee, 2Katherine Pauhl, 1Erika Harder, 2Tania Lam, 1James M. Wakeling1
1
Simon Fraser University, Burnaby, BC, Canada
2
University of British Columbia, BC, Canada
E-mail: [email protected]
INTRODUCTION
Locomotor training with body weight supported
treadmill training (BWSTT) is a commonly used
rehabilitation tool for retraining individuals with
incomplete spinal cord injury (SCI) [1]. It is often
augmented with robotic devices to assist leg
movements [2], however, there is recent evidence
that resistance to leg movements, instead of
assistive forces, results in increased flexor muscle
activity through enhanced afferent feedback [3]. As
sufficient foot clearance can be problematic for SCI
individuals, the timing of muscle activation is
crucial for normal gait. Electromyography (EMG) is
often used to measure muscle activity, in addition to
kinematics and kinetic measurements to evaluate
gait function. Recent methods of using wavelet
analysis to resolve EMG signals into frequency
components provide information beyond the
standard timing and amplitude measures [4,5]. The
purpose of this study is to investigate the influence
of BWSTT on co-activation between antagonistic
muscles using wavelet analysis.
METHODS
We tested individuals (n=7, 42.0±14.3 yrs,
1.75±0.12 m, 79.7±22.6 kg) who had incurred an
incomplete spinal cord injury due to a nonprogressive lesion above the thoracic level of T10,
at least 12 months prior to recruiting to the study.
Subjects were tested pre- and post- training where
they walked on a treadmill while in body weight
supported harness (the minimum support necessary)
at their self-selected comfortable and maximum
speeds. EMG data were collected bilaterally from
the tibialis anterior (TA), medial gastrocnemius
(MG), rectus femoris (RF), and biceps femoris (BF)
(Delsys, Boston, MA). Force sensitive resistors
were used to detect foot contact and toe-off. After
the initial visit, subjects participated in a BWSTT
program where they walked on a treadmill with a
harness that supported a percentage of their body
weight, while the Lokomat device applied velocitydependent moment against the hip and knee joints
in the sagittal plane that was scaled to their
maximum hip and knee flexor voluntary contraction
(Lokomat: Hocoma, AG, Volketswil, Switzerland).
All subjects underwent 45 minutes walking session,
three days a week, for a total of 36 sessions. Age-,
gender-, and height-matched healthy individuals
(n=10, 40.0±12.8yrs, 1.75±0.09m, 74.5±13.6kg)
were also tested at the same % body weight support
and velocities as their matched SCI. Data for
approximately 50 strides per subject from the preand post-training tests were analysed. EMG signals
were resolved into time-frequency components
using wavelet analysis [4,5]. The mean intensity at
each wavelet domain (10 wavelets ranging from
19.29 Hz to 395.4 Hz) was calculated to generate an
intensity spectrum. The correlation coefficient, r,
was calculated for the EMG intensities between
pairs of antagonistic muscles at each frequency
band to generate a correlation spectrum. The
intensity spectra and correlation spectra were
analysed using principal component analysis [5].
We calculated an EMG-normalcy score as the
resultant distance between the principal component
loading scores for each antagonistic muscle pair and
the mean principal component loading scores for the
control subjects. ANOVA was performed to
determine the effect of training, antagonistic muscle
pair, speed, gait phase, and subject (random) on the
mean correlation coefficient with Tukey post-hoc
tests when appropriate.
RESULTS AND DISCUSSION
For the TA-MG muscles, the correlation coefficient
of pre-training SCI was significantly greater than
that of healthy controls (p = 0.02) and tended to be
greater than that of post-training SCI (Fig. 1).
BWSTT decreased the correlation between the MGTA muscles especially at the mid-range frequencies
(Fig. 1). Correlation and coordination of the RF and
BF also improved after BWSTT (Fig. 1), although
not as substantially as the more proximal muscles.
The EMG normalcy-score, calculated from the PCI
and PCII loading scores (Fig. 2) were significantly
less after training for MG-TA (p = 0.03), indicating
that muscle function improved during training.
Correlation R2
0.2
MG-TA
0
-0.2
RF-BF
0.2
0
-0.2
100
200
300
Frequency (Hz)
400
Figure 1: Correlation spectra of EMG intensities
between muscles of healthy controls (blue), pretraining SCI (black), and post-training SCI (red) of
the antagonistic pairs of muscles: 1) medial
gastrocnemius (MG) and tibialis anterior (TA) and
2) rectus femoris (RF) and biceps femoris (BF).
PCII Loading score
MG-TA
-1.0
1.5
-
1.0
- 0.
5
RF-BF
Body weight supported treadmill training with
resistance at the hip and knee joints appears to
decrease the co-activation of the MG-TA muscles
during gait. We are currently analyzing a set of
similar data for a group of SCI individuals that
underwent BWSTT with assistive forces applied to
the hip and knee joints for comparison. Using
wavelet analysis, we can calculate the intensity and
correlation between antagonistic muscles over a
range of frequencies. This EMG method considers
the variation in frequency components in the EMG
signal and is therefore more informative of muscle
activity than traditional methods. This is useful in
developing and assessing training interventions as
specific frequencies can be targeted. Application of
this EMG analysis to quantify and evaluate muscle
dysfunction and coordination in SCI offers new
insights into the fundamental mechanisms behind
SCI impaired gait and into the effectiveness of
rehabilitation treatments.
CONCLUSIONS
Body weight supported treadmill training with
resistance at the hip and knee joints is an effective
rehabilitation training that improves co-activation of
antagonistic muscles. By employing advanced EMG
processing techniques such as wavelet analysis and
principal component analysis, information about the
frequency content of the EMG signal can be
obtained which is more informative that traditional
methods and provides insight into muscle
dysfunction and coordination in SCI individuals.
-1.0
1.0
REFERENCES
\
1.0
-1.0
-2.0
PCI Loading score
Figure 2: First and second principal component
(PCI and PCII) loading scores of intensity and
correlation spectra of healthy controls (blue), pretraining SCI (black), and post-training SCI (red) of
the antagonistic pairs of muscles: 1) medial
gastrocnemius (MG) and tibialis anterior (TA) and
2) rectus femoris (RF) and biceps femoris (BF).
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