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Electromyography of spinal cord injured rodents trained by neuromuscular electrical stimulation timed to robotic treadmill training

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Electromyography of spinal cord injured rodents trained by neuromuscular electrical stimulation timed to robotic treadmill training

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Content ELECTROMYOGRAPHY OF SPINAL CORD INJURED RODENTS
TRAINED BY NEUROMUSCULAR ELECTRICAL STIMULATION TIMED
TO ROBOTIC TREADMILL TRAINING
by
Sina Askari
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulllment of the
Requirements for the Degree
MASTER OF SCIENCE
(BIOMEDICAL ENGINEERING)
August 2012
Copyright 2012 Sina Askari
To my family
ii
Acknowledgments
First of all I would like to extend my appreciation to Dr. Deborah Won for her
work as my dissertation chair. I am truly indebted and thankful to her support.
I denitely could not have done this thesis without her encouragement and vast
knowledge of the dissertation process.
I would like to thank Dr. Norberto Grzywacz, Dr. Gerald Loeb and Dr. James
Weiland for agreeing to serve on my committee and their guidance and suggestions.
I would like to thank my second supervisor Dr. Ray de Leon for his assistance,
recommendations and guidance, for which I am extremely grateful.
I would also like to thank my colleagues and friends in NETlabber who helped
me in many ways for their assistance with animal surgeries and care. Gratitude is
also owed to the department of Electrical Engineering at California State University
Los Angeles for providing generous support and equipment. Additionally, I would
like to thank the NIH for funding this research.
Finally, I would like to express my gratitude to my family for their encourage-
ment, support and great patience at all times.
iii
Table of Contents
Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
Chapter 1: Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Spinal Cord Injury and Current Practice for Rehabilitation . 1
1.1.2 Robotic Treadmill Training (RTT) Therapy . . . . . . . . . 2
1.1.3 Neuromuscular Electrical Stimulation (NMES) Technology
and its Present Limitations . . . . . . . . . . . . . . . . . . 3
1.2 A New Approach to NMES . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Chapter 2: Experimental Design and Methods . . . . . . . . . . . . . . . . 6
2.1 The NMES+RTT System Design and Rationale . . . . . . . . . . . 6
2.2 Experimental Procedures . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3 Study 1: Comparing stimulation coordinated with RTT vs. pat-
terned stimulation alone . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.1 Subject Groups . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3.1.1 NMES+RTT . . . . . . . . . . . . . . . . . . . . . 9
2.3.1.2 Random Stimulation (RS) . . . . . . . . . . . . . . 10
2.3.2 Experimental Timeline . . . . . . . . . . . . . . . . . . . . . 10
2.3.3 Training Protocol . . . . . . . . . . . . . . . . . . . . . . . . 11
2.3.4 Testing Protocol . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4 Study 2: Comparing NMES+RTT with RTT alone . . . . . . . . . 11
2.4.1 Subject Groups . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4.1.1 NMES+RTT . . . . . . . . . . . . . . . . . . . . . 12
2.4.1.2 Robotic Treadmill Training (RTT) . . . . . . . . . 13
iv
2.4.2 Experimental Timeline . . . . . . . . . . . . . . . . . . . . . 13
2.4.3 Training Protocol . . . . . . . . . . . . . . . . . . . . . . . . 13
2.4.4 Testing Protocol . . . . . . . . . . . . . . . . . . . . . . . . 14
Chapter 3: Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.1 Step Trajectory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2 EMG Prole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Chapter 4: Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.1 Study 1: Comparing stimulation coordinated with RTT vs. pat-
terned stimulation alone . . . . . . . . . . . . . . . . . . . . . . . . 20
4.2 Study 2: Comparing NMES+RTT with RTT alone . . . . . . . . . 23
4.2.1 Intact EMG Prole . . . . . . . . . . . . . . . . . . . . . . . 23
4.2.2 Eect of RTT followed by NMES+RTT on EMG prole . . 24
4.2.3 Eect of NMES+RTT followed by RTT on EMG prole . . 25
Chapter 5: Discussion and Conclusions . . . . . . . . . . . . . . . . . . . . 33
5.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
5.2 Future Development . . . . . . . . . . . . . . . . . . . . . . . . . . 35
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
v
List of Tables
4.1 Comparison of
between groups . . . . . . . . . . . . . . . . . . . 22
4.2 Dierences in
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
4.3 Gaussian t parameters . . . . . . . . . . . . . . . . . . . . . . . . 28
4.4 Dierences in Gaussian t parameters with its signicance (p-value)
across groups and therapies . . . . . . . . . . . . . . . . . . . . . . 29
vi
List of Figures
2.1 System control schematic diagram . . . . . . . . . . . . . . . . . . . 7
2.2 Ankle trajectory and period of stimulation during training . . . . . 10
2.3 Study #1 timeline . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4 Stimulation coordinated to the step trajectory of rat hindlimb . . . 13
2.5 Study #2 timeline . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.1 Graphical User Interface (GUI) front panel . . . . . . . . . . . . . . 17
4.1 Overall average trajectory and EMG prole of an RS rat. . . . . . . 21
4.2 Overall average trajectory, EMG prole and applied stimulation of
an NMES+RTT rat. . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4.3 Sample EMG proles from each of the rats in the RS (a) and
NMES+RTT (b) group. . . . . . . . . . . . . . . . . . . . . . . . . 22
4.4 EMG prole and step trajectory from intact (untrained) rat . . . . 23
4.5 Sample EMG proles, and corresponding trajectory at baseline,
after 2 weeks RTT, and after a subsequent 2 weeks of NMES+RTT 25
4.6 Group 1 average EMG proles vs. % gait cycle at baseline, after
NMES+RTT, after RTT . . . . . . . . . . . . . . . . . . . . . . . . 26
4.7 Sample EMG proles, and corresponding trajectory at baseline,
after 2 weeks NMES+RTT, and after a subsequent 2 weeks of RTT 27
4.8 Group 2 average EMG proles vs. % gait cycle at baseline, after
NMES+RTT, after RTT . . . . . . . . . . . . . . . . . . . . . . . . 28
4.9 Changes in the shape of the EMG prole based on
measure between
group 1 and 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.10 An example of Gaussian t curve for a given rat from group 1 . . . 30
vii
4.11 An example of Gaussian t curve for a given rat from group 2 . . . 31
4.12 The parameter , the width of the Gaussian t curve . . . . . . . . 31
4.13 The parameter , the position of the centre Gaussian t curve . . . 32
4.14 The parameter A, the height of the Gaussian t curve . . . . . . . . 32
viii
Abstract
Neuromuscular electrical stimulation (NMES) has been used as a therapeutic tool
for patients of neuromotor dysfunction to eectively regain some motor functions.
It achieves this restoration of function by causing muscle contractions by applying
electrical impulses to peripheral nerves.
We have developed an NMES system for a rodent model of spinal cord injury
(SCI) with the long term goal of creating a therapy which restores control over
stepping back to the spinal circuitry. The therapy times NMES applied to the
tibialis anterior (TA) ankle
exor muscle at the initial portion of the swing phase
during robotic treadmill training (RTT) in an attempt to reinforce aerent activity
generated just during treadmill stepping.
Two studies were conducted to evaluate our proposed NMES+RTT therapy. In
the rst study, we compared the changes in electromyographic (EMG) activity of
spinally contused rats who received NMES timed to the aerent feedback generated
during robotic treadmill training (RTT) with rats receiving patterned NMES but
randomly timed with respect to their hindlimb movements. The results indicated
that stimulation appropriately timed to robotically treadmill training reshaped the
EMG prole such that the EMG energy was concentrated during the initial portion
of the swing phase, the same portion of the gait cycle during which stimulation
was applied during training; in contrast, patterned stimulation alone did not lead
to any consistent pattern in the EMG prole.
ix
We conducted a second study with a longitudinal cross-over design to compare
the eect of NMES+RTT on modications in EMG activity with that of RTT only.
On average, both types of training helped to modulate TA EMG activity over a gait
cycle, resulting in more consistent EMG proles across steps with peaks occurring
just before or at the beginning of the swing phase, when ankle
exion is most
needed. RTT appeared to be important for helping rats to generate appropriate
muscle activation for stepping. However, NMES+RTT resulted in EMG activation
being concentrated during the initial swing phase more than RTT only. We also
studied the stepping trajectory performances of each individual rats within each
group. The result suggests that NMES+RTT therapy exhibits more consistent
stepping and more like pre-programmed trajectory. These improvements were
consistent with the notion that NMES timed appropriately to hindlimb stepping
could help to reinforce the motor learning that is induced by aerent activity
generated by treadmill training.
The work presented in this thesis contributes to a better understanding of how
NMES therapy could be designed to induce long-term changes in motor control of
stepping and thus eventually lead to a therapy to better rehabilitate walking in
spinal cord injury patients.
x
Chapter 1
Introduction
1.1 Motivation
1.1.1 Spinal Cord Injury and Current Practice for Reha-
bilitation
There are approximately 1,275,000 individuals in the United States that they have
traumatic spinal cord injuries(SCI) [1, 6]. Aside from the obvious debilitating
eects of paralysis and loss of sensation, the lack of mobility leads to many other
serious health problems including pressure sores, circulatory dysfunction, and car-
diovascular disease [34, 38, 20].
Studies have provided evidence that SCI patients can recover some of their
motor function with appropriate training. Because the spinal cord is capable of
remodeling itself, and activity can help shape and induce some of that remodeling
[4, 35, 15], it is possible for therapies, if appropriately designed, to help restore
some of the capabilities that were lost due to spinal cord injury. Conversely, as
spinal circuits are used less and less for walking, they become less capable of
generating walking. This property of the spinal cord that allows itself to adapt in
accordance with activity and stimulation post-injury is called activity-dependent
plasticity [4, 35, 24]. Activity-dependent spinal plasticity can be triggered by
1
sensory stimulation during training. As an individual performs walking, the spinal
cord receives sensory feedback from mechanoreceptors which convey information
about stretch, pressure, touch, and proprioception [4, 35]. After spinal cord injury,
sensory feedback plays an important role in remodeling the spinal circuitry and
strengthening synaptic connections (e.g., [5]). Studies indicate that the sensory
input must be coordinated with the timing of the gait cycle in order to generate the
correct output [4, 23]. We hypothesize that this activity-dependent plasticity could
be more eectively induced by applying electrical stimulation with the appropriate
timing to the gait cycle.
1.1.2 Robotic Treadmill Training (RTT) Therapy
Body-weight supported treadmill training is one method for helping SCI patients to
regain some of their ability to walk. The patient is strapped into a harness attached
to a boom which supports a designated percentage of the patient's body weight.
A physical therapist helps to move the patient's legs through gait cycles while
the treadmill is turned on. Robotic treadmill training (RTT) was developed to
allow the patient to perform treadmill training without the assistance of a physical
therapist and also to be able to more carefully control the assistance provided
during step training [8]. In RTT, the patient wears a leg orthosis which drives
his/her leg through a programmed trajectory.
Treadmill training has already been shown to improve stepping in spinal cord
injured animals [22, 9]. The mechanisms by which this occurs are unknown; how-
ever, recent evidence suggested that training the hindlimbs induced activity that
enhanced synaptic plasticity within the locomotor-generating circuitry of the spinal
cord [29]. Other studies have shown the importance of aerent feedback in pro-
moting rehabiliation of stepping [36].
2
1.1.3 Neuromuscular Electrical Stimulation (NMES) Tech-
nology and its Present Limitations
Neuromuscular electrical stimulation (NMES) or functional electrical stimulation
(FES) is a biomedical therapy by which electrical stimulation is applied to periph-
eral nerves to articially generate muscle activation. For example, NMES is applied
to leg muscles in SCI patients to provide muscle contractions needed to generate
walking [18, 30, 2, 17, 13, 31]. NMES has generally been designed to have an
immediate eect on muscles [28, 3] namely, stimulation triggers muscle activation
and results in some functional output that has been impaired or lost due to neuro-
logical damage. Commercial FES systems presently stimulate peripheral nerves at
pre-set times relative to the initiation of a gait cycle. These devices were designed
to serve immediate needs, analogous to a walking crutch, in that once the stim-
ulation is taken away, the articially triggered muscle activations which aid with
walking are also expected to disappear. While these pre-programmed FES systems
have enabled patients to stand and walk short distances, the high energy expen-
ditures and fatigue induced by FES have limited their eectiveness as a mobility
aid [31, 28, 37] Furthermore, the FES systems that have been used for ambulation
produce an unnatural gait [37, 7, 31].
1.2 A New Approach to NMES
There has been some evidence that NMES during assisted walking (i.e., while
using a crutch, cane, or walker) can eect kinematic changes that remain even
after stimulation has terminated [3]. Yet, to our knowledge, no NMES system has
been designed specically to reinforce the spinal cord circuitry by appropriately
timing stimulation to robotically-assisted limb movements and thereby eect long-
term improvements in walking. A few studies have investigated combining NMES
3
with body weight supported treadmill training (BWSTT). In one case, NMES
was applied to activate ankle
exion during the swing phase of each gait cycle to
prevent the foot from dragging and impeding the swing phase while the patient
was performing BWSTT [16]. In another case, a robotically assisted treadmill
training system was used to provide the gait initiation cue for the pre-set NMES
timing during each gait cycle [11].
We propose a design for NMES therapy, also in a rodent model, but which will
provide adaptive control for timing stimulation of aerent pathways to generate
eective stepping during training and eerent pathways to reinforce spinal circuitry
during eective stepping. An RTT device was developed for a rodent model of SCI
in order to conduct animal experiments in gait rehabilitation. This device oers
a few key features that we exploit in the design of our therapy: 1) the ability
to guide the animals' hindlimbs through pre-programmed trajectories, such that
if the therapy is capable of reinforcing gait patterns, the stimulation is applied
during desirable stepping activity; 2) the ability to control the level of assistance;
and 3) the ability to sense the actual hindlimb position.
Another group has developed an NMES system for testing rehabilitative eects
of stimulation alone in a rodent model of spinal cord injury, and has already
presented results which indicate that stimulation alone over the course of 7 days
can lead to improvements in limb coordination. As in [21], we developed this
system for a rodent model of spinal cord injury in order to better enable long-term
studies of NMES as a rehabilitation tool for walking and the underlying eects on
spinal plasticity.
However, in contrast to their system in which stimulation is applied to generate
cyclical
exion/extension patterns while the rats are suspended, such that there is
no load bearing during training, we coordinate NMES to weight-bearing treadmill
4
stepping in an attempt to reinforce aerent activity produced during training so
that the spinal cord is better enabled to generate stepping when assistance is
removed. Our NMES+RTT system is designed to coordinate stimulation with
hindlimb stepping and allow more precise control over the stimulation. In order to
do so, stimulation control is integrated into a robotic treadmill training program,
so that, for example, stimulation could be more precisely timed to continuously
monitored hindlimb position. The goal of this new approach is to eect long term
changes in spinal cord circuitry. It will also advance our understanding of the
interaction between applied electrical stimulation and the human nervous system,
which will in turn advance the development of existing therapies to impact a range
of neurological disorders.
1.3 Objectives
Recent studies have investigated the rehabilitative eect of NMES on stepping
and whether NMES promotes independent stepping ability [26, 21]. To address
the aforementioned limitations of present NMES technology, we are developing
a new NMES system which times stimulation to robotically controlled hindlimb
position in spinal cord injured rodent animals during stepping.
Our long-term aim in combining NMES with robotically controlled treadmill
training (RTT) is to enhance activation of the spinal cord circuitry that controls
gait. To achieve this goal, an NMES system was engineered to integrate infor-
mation from the robotically controlled position during stepping in order to time
stimulation to continuous gait information from the rat.
5
Chapter 2
Experimental Design and Methods
2.1 The NMES+RTT System Design and Rationale
A new NMES therapy was developed which times stimulation according to the
desired hindlimb trajectory during robotically assisted treadmill training (RTT)
(see Figure. 2.1). In RTT, a rat steps on a moving treadmill while strapped into a
harness which provides body weight support. The hindlimb movements are guided
by robotic arms attached to the ankle. The robot applies a servomotor feedback
controlled force to the hindlimbs when the ankle deviates from the pre-programmed
(desired) trajectory by more than a designated window of error.
Figure 2.1 illustrates the system control block diagram. The main controller was
comprised of a LabView program which integrated the robotic software program.
This software communicates between the stimulator (S88x, Grass Technologies,
West Warwick, RI) and the robotic instrumentation. The entire program runs
in a LabView interface (National Instruments, Dallas, TX). When the program
is executed, rst a LabView virtual instrument (VI) is launched which acts as
the host controller for setting the stimulus parameters. This main controller was
responsible for the following functions: 1) controlling treadmill speed; 2) recording
TA EMG activity; 3) controlling the stimulator; 4) controlling BWS; 5) controlling
6
the force applied to the hindlimbs to guide the step trajectory as well as sensing
actual hindlimb position.
Figure 2.1: System control schematic diagram
During NMES+RTT therapy, biphasic current pulse trains (70pps, 100s pulse
width, and 1.5 times the animals motor threshold) were delivered to the TA while
the rat was performing RTT. The stimulation was timed occur, according to opti-
cally sensed ankle position, during the rst 50% of the swing phase, as shown in
Figure. 2.2. However, if the rats ankle position did not follow the programmed
pattern suciently, as dened by the correlation coecient between desired and
actual trajectory in the past 50ms, then the stimulation was aborted.
The proposed approach is to time stimulation to robotically controlled move-
ments of the hindlimb. The rationale is that by stimulating neural pathways
between the spinal cord and muscles at appropriate times, the therapy will rein-
force spinal circuits which generate stepping. This approach is based on evidence
of two principles: 1) that appropriately timed aerent activity during stepping
in
uences and is important for spinal reorganization [4, 23, 14]; and 2) that invok-
ing activity-dependent plasticity also requires that the hindlimb stepping that we
desire to reinforce is coincident with the stimulation therapy [25, 19, 27]. Thus,
7
by applying stimulation when aerent activity is expected to be naturally gener-
ated from weight-bearing stepping, and only applying it if the rat is stepping well
(according to our correlation measure), the therapy is expected to reinforce spinal
circuitry which is involved in generating well-formed steps.
2.2 Experimental Procedures
Rats were spinally contused with a force impactor (Precision Systems & Instru-
mentation, Lexington, KY) at the mid-thoracic (T9) level. The force impactor
delivered a 250 kdyn downward force directly onto the spinal cord in order to
induce a severe spinal contusion injury. Two weeks later spinally contused rodents
were implanted with electrodes to stimulate nerves innervating ankle
exor mus-
cles (i.e., the tibialis anterior). The surgical procedures were similar to those used
in [10] and are brie
y described here. Te
on-coated wires were tunneled subcu-
taneously, through a 23-gauge hypodermic needle, along the back of the animal
from the headplug cemented on the skull to the hindlimb tibialis anterior (TA).
Approximately 1-2 millimeter of the Te
on coating was scraped away to expose
bare wire along the muscle belly. Appropriate positioning of the electrode was
tested by eliciting a twitch response with electrical stimulation applied through
the electrode. The wire electrode was sutured in place at the points of entry into
and exit from the muscle.
Two studies were conducted to evaluate the capability of our NMES+RTT to
rehabilitate stepping after spinal cord injury and to gain insight into the neuro-
muscular changes underlying these rehabilitative eects. In the rst study, changes
in EMG of spinally contused rats who received NMES+RTT were compared with
those of rats receiving only stimulation. The focus of this work was to test the
eect of synchronizing stimulation to stepping as opposed to delivering the same
8
patterned stimulation but while the rats were mostly stationary. In the second
study, the eects of the NMES+RTT therapy were compared to RTT alone. The
experimental design of these two studies are described separately in the following
sections.
2.3 Study 1: Comparing stimulation coordinated with
RTT vs. patterned stimulation alone
2.3.1 Subject Groups
Eleven rats were spinally contused and implanted with wire electrodes. The
rats were divided into two groups: 1) a robotic treadmill training-based NMES
(NMES+RTT) group (N=6); and 2) a random stimulation (RS) group (N=5).
2.3.1.1 NMES+RTT
NMES+RTT animals received stimulation which was timed to the robotically
detected swing phase of the gait cycle. The rats received this NMES+RTT train-
ing over 1000 gait cycles per training session. The program which controls the
RTT device was modied to output a trigger for stimulation to occur during the
upswing of the gait cycle as shown in Figure. 2.2. Thin gray traces in the back-
ground shows the trajectory of all the steps in one sample training session of an
NMES+RTT rat. Y is the vertical position and X the horizontal position of the
ankle. The green solid trace is the average trajectory. The portion of the gait cycle
during which stimulation was applied is indicated on the average trajectory by red
asterisks.
The main controller for the stimulator (Grass Instruments, S88x) was devel-
oped in LabView (National Instruments). The LabView virtual instrument (VI)
9
Figure 2.2: Ankle trajectory and period of stimulation during training
monitored the trigger signal from the robot program and accordingly turned the
stimulator on and o through a USB interface as depicted in Figure. 2.1.
2.3.1.2 Random Stimulation (RS)
RS animals did not undergo treadmill training; in contrast to the NMES+RTT
group, RS rats received electrical stimulation while they were in their cages, not
during stepping. A phantom simulated the presence of a rat in the robotic treadmill
device, and the NMES+RTT therapy was turned on to deliver stimulation in
the same pattern as would be delivered to a rat that did not resist the robotic
control. In other words, the RS animals were stimulated with the same stimulation
pattern as a rat which was stepping with a trajectory that roughly matched the
programmed desired trajectory. Thus, both groups received patterned stimulation
that is in phase with a stepping pattern, but the NMES+RTT stimulation was
coordinated with the rat's actual stepping patterns, while the RS stimulation was
randomly timed with respect to the rat's hindlimb movements.
2.3.2 Experimental Timeline
Group 1 (n=6) received 2 weeks of a robotic treadmill training-based NMES
(NMES+RTT), while Group 2 (n=5) received random stimulation therapies in
case (Figure. 2.3).
10
Day -14 Spinal Cord Injury
Day -7 Electrode Implant
Day 0 Post Injury Baseline
Day 1-28 (RS)
Training
Day 29 RS testing
(a) RS
Day -14 Spinal Cord Injury
Day -7 Electrode Implant
Day 0 Post Injury Baseline
Day 1-28 (NMES+RTT)
Training
Day 29 NMES+RTT testing
(b) NMES+RTT
Figure 2.3: Study #1 timeline
2.3.3 Training Protocol
Stimulation was applied for a total of four minutes of stimulation each day for 2
weeks during treadmill training (NMES+RTT) or in cages (RS).
2.3.4 Testing Protocol
Testing was performed at the conclusion of the 2 weeks of training. Rats in both
groups were placed in the body weight support harness while the treadmill was
turned on at 8cm=s. The animal performed unassisted treadmill stepping; i.e., the
animal was placed on the treadmill with body weight support but no robotic assis-
tance or electrical stimulation were applied to the hindlimbs. EMG was recorded
from the rats while they were performing the treadmill stepping. The hindlimb
position was simultaneously acquired through the robot. Each rat was tested for
a total of 2 minutes. During testing, the ability to perform independent stepping
without any assistance was assessed.
2.4 Study 2: Comparing NMES+RTT with RTT alone
2.4.1 Subject Groups
Twenty rats were spinally contused and implanted with wire electrodes. Seventeen
rats survived the spinal cord injury long enough to complete training; electrode
11
implants remained intact in 14 animals out of those 17 for the course of the study.
The rats were divided into two groups: 1) received 2 weeks of RTT only followed
by NMES+RTT group (n = 8); and 2) received therapies in the reverse order
(n = 6).
2.4.1.1 NMES+RTT
During NMES+RTT therapy, the robot guides the rat ankle along a pre-
programmed trajectory (solid blue trace) as shown in in Figure 2.4. The stimulator
is timed occur, according to optically sensed ankle position. The stimulation is pro-
grammed to turn on for a portion of the "upswing" stage of each gait cycle, which
we dene as occurring from toe o until the rat raises its hindlimb to optimum
swing position, as shown in the red dotted traces in Figure 2.4.
A biphasic current pulse trains (70pps, 100s pulse width, and 1:5 times the
animals motor threshold) are delivered to the TA while the rat is performing
RTT. However, if the rats ankle position did not follow the programmed pattern
suciently, as dened by the correlation coecient between desired and actual
trajectory in the past 50ms, then the stimulation is aborted. The correlation
estimate of the were calculated following the formula detailed in Equation 2.1.

x
(n) =corr(x
des
;x
snes
) =
n
X
i=nL+1
(x
des
(i) x
des
)(x
snes
(i) x
sens
)
(L 1) s
des
s
sens

y
(n) =corr(y
des
;y
snes
) =
n
X
i=nL+1
(y
des
(i) y
des
)(y
snes
(i) y
sens
)
(L 1) s
des
s
sens
(2.1)
12
Figure 2.4: Stimulation coordinated to the step trajectory of rat hindlimb
2.4.1.2 Robotic Treadmill Training (RTT)
A previous study [22] showed providing low levels of assistance was more benecial
to rehabilitating stepping than rigid robotic control. Thus, the robot was pro-
grammed to apply forces only if the rat deviated more than 1cm from the desired
trajectory. For RTT therapy, 85% of the rats body weight is supported while robot-
ically controlled arms guide the rats ankle according to a pre-programmed trajec-
tory to step on a treadmill moving at 6cm=s. During RTT, forces by robot arms
were only imposed if the ankle deviated more than 1cm from the pre-programmed
robot trajectory.
2.4.2 Experimental Timeline
Group 1 (n=8) received 2 weeks of RTT only followed by NMES+RTT, while
Group 2 (n=6) received therapies in the reverse order (Figure. 2.5).
2.4.3 Training Protocol
For RTT alone, rats were strapped into a body weigh support, and the robot
controls the stepping over the two-week course of RTT control by the observer,
100 loops of stepping (approximately four minutes per session) per rat each day.
13
Day -14 Spinal Cord Injury
Day -7 Electrode Implant
Day 0 Post Injury Baseline
Day 1-14 (RTT)
Therapy
RTT testing
Day 15-28 (NMES+RTT)
Therapy
Day 29 NMES+RTT testing
(a) Group 1
Day -14 Spinal Cord Injury
Day -7 Electrode Implant
Day 0 Post Injury Baseline
Day 1-14 (NMES+RTT)
Therapy
NMES+RTT testing
Day 15-28 (RTT)
Therapy
Day 29 RTT testing
(b) Group 2
Figure 2.5: Study #2 timeline
In addition for NMES+RTT, stimulation was applied for a total of four minutes
of stimulation each day for 2 weeks during treadmill training.
2.4.4 Testing Protocol
Post injury testing was performed after rats had approximately 2 weeks to recover
from spinal cord injury. Testing was performed again after the rst two weeks of
rst training and after the following two weeks of second training (a total of 4
weeks after the post injury testing). During testing, rats received neither electrical
stimulation nor robotic assistance.
14
Chapter 3
Data Analysis
Raw EMG and position data were synchronously stored for post processing analysis
in MATLAB (Mathworks, Natick, MA) for the purpose of both step detection and
EMG prole analysis.
3.1 Step Trajectory
The beginning of a step cycle was computed as the time of the negative peaks in
the horizontal position signal (x). Local minima were detected as zero-crossings
of the rst-order dierence with a step size of 5 (i.e., x[k + 5] - x[k]). This also
demarcated the beginning of the swing phase, also known as toe o (TO). Stance
phase is dened as the time from paw contact (PC) to toe o. Typically PC can be
dened as the time at which x reaches its maximum; i.e. time of the positive peak
in x. However, because of the abnormal trajectory of the rats (Figure 2.2), PC was
determined by nding the rst point at which y reached 0 after a positive peak in
x. The continuous x and y signals were divided into step cycles, dened between
consecutive TO events. The PC within each step cycle demarcated the boundary
between swing phase and stance phase. These TO and PC times were then used
to also dene steps, as well as the swing and stance phases, in the synchronously
acquired EMG. Steps which did not reach a height of 30 mm (i.e., the y range
15
within a given step did not reach a certain threshold) were not considered valid
steps and were excluded from analysis.
3.2 EMG Prole
Raw EMG was amplied by 1000x followed by bandpass ltered (0.1-3 kHz). Enve-
lope detection was then performed on these digitized EMG using full-wave recti-
cation and a moving average lter (window length = 25 ms).
The average EMG prole during a gait cycle was computed for each step for
each rat. The duration of each step varied a lot between individual subjects
(mean +s:d: = 945 + 637ms), so to compare the EMG prole across a single
gait cycle, the duration of each EMG segment for a given step was normalized to
the longest step duration [33, 32, 12]. In order to carry out this normalization, the
EMG segments during each gait cycle were linearly interpolated (using MATLAB's
predened function interp1); i.e., if the longest step in duration had a length of
L samples, each EMG segment length was normalized to L samples. The individ-
ual EMG proles for all the extracted steps were averaged to create the average
EMG prole for a given rat. Stimulation during training was applied from 0% to
approximately 50% of the swing cycle.
A graphical user interface (GUI) was developed for the purpose of EMG analysis
(see Figure. 3.1). The EMG prole was computed in two steps. The rst step
is to extract all steps with an automated step detection scheme as described in
section 3.1. The GUI waits for the user to validate the automated parameters for
step detection such as window size threshold for peak detection, and whether to
use TO or PC as the start of the gait cycle. The second step is to identify only
those valid step cycles to be included in creating EMG proles. The user can select
any subset of the steps to include in the EMG prole; we dened a minimum x
16
and y displacement of 5mm in order to be considered a step. An overlay plot of
all left/right EMG and trajectory signals were shown in the top two panels. The
parallel vertical dashed pink lines indicates the start and end of each individual
steps. The EMG and position signals during each step were time-normalized to the
longest duration step cycle using MATLABs linear interpolation function. Finally
an ensemble average of EMG proles and step trajectories were computed for the
selected steps, shown in the bottom two graphs for left/right leg.
Figure 3.1: Graphical User Interface (GUI) front panel
In Study #1 the concentration of EMG activity during the corresponding period
during testing was quantied, as described by Equation 3.1. Where s is the EMG
prole of a given rat, and s is the average EMG prole for a given group, is the
percent gait cycle, g is the proportion of the gait cycle represented by the swing
phase, and
is the percentage of EMG activity concentrated from 0% to 50% of
the swing cycle
17

=
50%g
R
0%
s() d
100%
R
0%
s() d
100 (3.1)
In Study #2, we were able to measure EMG during stepping from one rat before
injury and training; its step trajectory was qualitatively good. We computed its
EMG prole and refer to it as the \intact EMG prole" against which other EMG
proles can be compared. We also adjusted the integration limits in the
measure
(Equation. 3.1) so that it represents how much the EMG activity is concentrated
in the same portion of the gait cycle as in the intact EMG prole. This intact
EMG prole typically rises from about 10% of the gait cycle before the beginning
of the swing phase peaking near the beginning of the swing phase, and decreasing
until about 50% of the swing cycle (see Figure. 4.4. These boundary points were
quantitatively determined by evaluating the cumulative EMG energy as the limits
were adjusted (i.e., evaluating the numerator of theg equation) and determining at
which limits the slope increased most and decreased most. Therefore, in study #2
we re-dened the
integration limits to re
ect the concentration of EMG energy
during this portion of the gait cycle at which the intact EMG prole tends to peak,
as shown in Equation. 3.2.

=
50%g
R
10%
s() d
100%
R
0%
s() d
100 (3.2)
The peak in the EMG prole was more variable in study #2, perhaps as a result
of administering more
exible training such that the rat was permitted to deviate
more from the desired trajectory before robotic assistance was applied as training
18
progressed. Thus, using the
measure with xed integration limits did not seem
to provide an accurate assessment of how the therapy was or was not shaping and
aecting the EMG prole. Thus, an alternative method was used to assess how
well the EMG prole activity was concentrated in a particular portion of the gait
cycle. The EMG prole for each gait cycle was well modelled by a Gaussian t
curve as given in Equation. 3.3 (using MATLAB's predened function t - curve
tting toolbox). To obtain the least-squares minimization, the parameter was
limited to the scale of [0; 1] (representing 0 to 100% of the gait cycle, relative to
toe-o. A or (
1
p
2
) is the maximum intensity of the tted Gaussian curve for a
given EMG activity prole, is the center of the Gaussian t peak, and is the
width of the Gaussian peak.
^ s(g) =
1
p
2
exp
1
2
(
g

)
2
(3.3)
19
Chapter 4
Results
4.1 Study 1: Comparing stimulation coordinated with
RTT vs. patterned stimulation alone
Figure 4.1(c) and (d) show the average EMG prole from the left and right legs,
respectively, of an example RS rat during a complete gait cycle, dened as toe o
to toe o. The corresponding average trajectories are also shown (Figure. 4.1 a
and b). The green x indicates where the start of the swing phase was detected
(i.e., TO), while the red circle indicates the start of the stance phase (i.e., PC).
Swing phase occurs from toe o (green dashed line) until paw contact (red dashed
line). Stance phase occurs from paw contact to the next toe o (green dashed line
to 100% of the gait cycle). Analogously, Figure 4.2 illustrates the overall average
EMG prole and trajectory from left and right legs of the NMES+RTT group. The
overall average EMG prole of RS group has multiple peaks, and the left and right
side do not have much consistency with one another aside from a large peak toward
the end of stance; whereas that of the NMES+RTT group has generally one large
peak, which occurs at the beginning of the swing phase. Figure 4.2(e) and (f) shows
the stimulation prole when stimulation would have been applied within each gait
cycle during training. This peak in the NMES+RTT prole occurs approximately
20
in the same period during which stimulation was applied during training (Figure.
4.2 e and f); i.e., during the upswing of the swing phase (Figure. 2.4).
Figure 4.1: Overall average trajectory and EMG prole of an RS rat.
Figure 4.2: Overall average trajectory, EMG prole and applied stimulation of an
NMES+RTT rat.
Figure 4.3(a) shows the average EMG prole of each rat in the RS group during
testing. Peaks in EMG were observed to occur unpredictably at dierent points in
the gait cycle and could often have multiple peaks. In contrast, the EMG prole
21
of NMES+RTT Figure. 4.3(b) exhibited a much more organized and predictable
pattern; namely, there was generally one peak in the prole, and the peak generally
occurred at the beginning of the swing phase. A comparison of
between groups
is shown in Table 4.1. The NMES+RTT group had signicantly greater
values
on average than the RS group (one-way ANOVA F (1; 26) = 35:7;p<<:01).
Figure 4.3: Sample EMG proles from each of the rats in the RS (a) and
NMES+RTT (b) group.
Table 4.1: Comparison of
between groups
RS NMES+RTT
mean(
) 26% 55%
stdev(
) 13% 12%
22
4.2 Study 2: Comparing NMES+RTT with RTT alone
4.2.1 Intact EMG Prole
The intact EMG prole, obtained by the methods described in Section 3.2, pro-
vided a reference against which to compare EMG proles in this study. The com-
parison was quantied by the coecient of determinationR
2
between a given rat's
average EMG prole for a certain testpoint and the intact EMG prole. How-
ever, rats which we observed to qualitatively step well seemed to have a peak in
their EMG prole which did not necessarily peak at exactly the same percent gait
cycle as the intact EMG prole and was not necessarily the same width peak.
There did, however, seem to be a common feature amongst the EMG proles
of \good-stepping" rats. Both the intact EMG prole and the proles of rats
from Study 1 which exhibited other indicators of good stepping (e.g., consistent
burst-to-step latency, longer step lengths, step trajectories which better matched
the pre-programmed step trajectory) exhibited a dening characteristic; namely,
a single peak near the beginning of swing phase onset (i.e., near toe-o) (Figure.
4.4).
Figure 4.4: EMG prole and step trajectory from intact (untrained) rat
In order to quantify how well the EMG prole possessed this \ideal" charac-
teristic of the intact EMG prole, we t a Gaussian curve to the EMG prole, as
23
described in section 3.2. We measured the intensity A, mean (, the location of
the peak) and standard deviation (, the width of the peak) parameters of the t.
(parameters for the intact rat: A = 0:73, = 0:28, = 0:15). We hypothesized
that NMES+RTT would lead to EMG proles with a narrower peak which more
consistently occured near the beginning of the swing phase; i.e., we would expect
to be closer to 0%, the standard deviation of across steps for a given rat to be
smaller, and to be smaller.
4.2.2 Eect of RTT followed by NMES+RTT on EMG pro-
le
Figure 4.5 shows an example of the EMG prole at testing time point (baseline,
2-week testing, and 4-week testing) for a rat. Above each EMG prole plot is
a plot of the average trajectory. The dashed traces in the trajectory plots show
a random sampling of individual steps, while the solid red bold trace shows the
average trajectory. In the EMG prole plots, the gray outline indicates the 90%
condence interval across the EMG proles; the dashed vertical red line shows the
end of the swing phase or beginning of stance.
The EMG prole of the sample rat shown in Figure. 4.5, at baseline did not
show much of a peak and was relatively
at through the gait cycle (
=37.9%).
Correspondingly, the rat produced a very disorganized stepping pattern. After two
weeks of RTT only, the rat exhibited a sharper EMG prole (
=46.7%) accompa-
nied by more organized stepping patterns which more closely matched the desired
trajectory. The peak, starting from a short preparation period before the swing
phase through the early portion of the swing phase, became even sharper by the
end of two weeks of NMES+RTT (
=56.1%); in conjunction, the rat was still
stepping with consistency and additionally producing longer steps.
24
Figure 4.5: Sample EMG proles, and corresponding trajectory at baseline, after
2 weeks RTT, and after a subsequent 2 weeks of NMES+RTT
Figure 4.6 illustrates the average EMG proles of the left and right hindlimbs
at baseline, 2-week testing (after RTT), and 4-week testing (after NMES+RTT),
plotted vs. % gait cycle. EMG proles of individual rats (faint gray), group mean
(bold solid red), and 90% CI (black shadow).
4.2.3 Eect of NMES+RTT followed by RTT on EMG pro-
le
Figure 4.7 shows an example of the EMG prole at testing time point (baseline,
2-week testing, and 4-week testing) for a sample Group 1 rat. The annotations
used in the plot are described in the previous section sample plot from the other
group. Analysis of baseline test results revealed a disorganized EMG prole (
=27.0%) accompanied by dragging and poor stepping at baseline. The EMG
prole improved to a much more organized EMG prole (
=47.5%) and the steps
25
Figure 4.6: Group 1 average EMG proles vs. % gait cycle at baseline, after
NMES+RTT, after RTT
more closely matched the desired trajectories (with the ankle being lifted higher
and farther throughout the swing phase) with two weeks of NMES+RTT. Two
additional weeks of RTT only did not lead to improvements in the step trajectories
and led to more variable EMG prole with a lower
value (
=35.6%).
Figure 4.8 illustrates the average EMG proles of the left and right hindlimbs
at baseline, 2-week testing (after NMES+RTT), and 4-week testing (after RTT),
plotted vs. % gait cycle.
This trend was observed more generally across rats in each group. Figure 4.9
shows that average
for Group 1 increased by 3.5% with 2 weeks of RTT and
an additional 2.6% after 2 weeks of NMES+RTT; whereas the average Group 2
increased by 4.5% after 2 weeks of NMES+RTT and when followed by 2 weeks of
RTT
only improved by 0.8%. The increase in the concentration of EMG activity
during the early portion of the swing phase, relative to baseline gamma values,
26
Figure 4.7: Sample EMG proles, and corresponding trajectory at baseline, after
2 weeks NMES+RTT, and after a subsequent 2 weeks of RTT
was statistically signicant after NMES+RTT (paired t-testp<:01) but not after
RTT training (p = :10) (see Table. 4.2). The amount of improvement achieved
by each type of training appears to be state-dependent in that it depended on the
order in which the two therapies were applied.
Table 4.2: Dierences in
95%CI p value

% NMES +RTT vs: untrained [6:8%; 35:2%] 0.005

% RTT vs: untrained [2:0%; 25:8%] 0.089

NMES +RTT vs:
RTT [3:9%; 22:1%] 0.168
Figure 4.10 and 4.11 shows an example superimposed of EMG proles repre-
sented by Gaussian t lines during baseline, 2-week testing, and 4-week testing,
plotted vs. % gait cycle.
27
Figure 4.8: Group 2 average EMG proles vs. % gait cycle at baseline, after
NMES+RTT, after RTT
The parameters A, and for Gaussian t curve were displayed longitudi-
nally over time for each therapy in Figure. 4.12, 4.13, 4.14. These ndings are also
presented numerically in Table 4.3 , and dierences with their signicant values
in Table. 4.4. From computed trend, one nds that the improvement was signif-
icant from baseline to NMES+RTT as compare to RTT therapy alone showing a
narrower peak as well as center t curve shifted towards the toe o.
Table 4.3: Gaussian t parameters
Baseline 2weeks 4weeks
Amp (A) G1 0.206 0.312 0.373
G2 0.253 0.216 0.283
G1 0.148 0.102 0.139
G2 0.173 0.089 0.085
G1 1.325 0.554 0.275
G2 1.374 0.759 0.637
28
Figure 4.9: Changes in the shape of the EMG prole based on
measure between
group 1 and 2
Table 4.4: Dierences in Gaussian t parameters with its signicance (p-value)
across groups and therapies
NMES-RTT vs. RTT Group1 vs. Group2
parameter Group1 Group2 NMES-RTT RTT
j(A)j 0.046 0.10 0.097 0.038
p=0.50 p=0.16 p=0.24 p=0.45
j()j 0.077 0.046 0.12 0.04
p<< 0:01 p=0.02 p<< 0:003 p=0.43
j()j 0.35 0.49 0.21 0.64
p=0.38 p=0.05 p=0.23 p=0.33
29
Figure 4.10: An example of Gaussian t curve for a given rat from group 1
30
Figure 4.11: An example of Gaussian t curve for a given rat from group 2
Figure 4.12: The parameter , the width of the Gaussian t curve
31
Figure 4.13: The parameter , the position of the centre Gaussian t curve
Figure 4.14: The parameter A, the height of the Gaussian t curve
32
Chapter 5
Discussion and Conclusions
5.1 Summary
The results presented in this thesis demonstrates the lasting eect of a new biomed-
ical therapy which combines NMES and robotic treadmill training on neuromus-
cular output involved in producing locomotor activity. Results from study #1
showed that for rats which received the position-based NMES therapy during a
2-week training period, peak EMG activity was found to occur most often dur-
ing a window from 0% of the gait cycle (start of the swing phase) until roughly
halfway through the swing phase during treadmill stepping even when stimulation
was o. This corresponded to approximately the same period during which stimu-
lation was applied during training. In contrast, when RS rats performed treadmill
stepping without stimulation, the EMG prole exhibited peaks inconsistently at
random times with respect to the gait cycle. As can be seen by comparing Figure
4.1 (a) and (b) with Figure 4.2 (a) and (b), the swing and stance phases cover
similar portions of the overall trajectory in both groups; hence, any dierences in
when stance and swing phase occur in the two groups are not likely to explain
the obvious dierences in EMG proles. These results indicate that NMES+RTT
helps to improve step kinematics and underlying EMG patterns more than the
same patterned stimulation alone. Both the NMES+RTT and RS groups received
33
patterned stimulation, but a major dierence between groups was that the in the
latter, step-generated aerent feedback was absent during stimulation, suggesting
that timing the stimulation to aerent feedback generated during stepping pro-
motes long-term changes in neuromotor control of stepping.
These results are consistent with the concept of activity-dependent plasticity,
by which recovery of a particular function post-injury is enhanced by consistently
performing that function. In comparison with rats who received randomly timed
stimulation, rats who received stimulation appropriately timed to their stepping
activity over a signicant training period more reliably produced the EMG prole
that matched the stimulation pattern during training. Production of such an EMG
prole is an indication that NMES+RTT rats were better enabled to perform
proper stepping even without stimulation than RS rats, and that rehabilitation of
stepping was enhanced in NMES-RTT rats.
The results from study #2 showed that on average, both NMES+RTT and
RTT alone helped to modulate TA EMG activity over a gait cycle, resulting in
more consistent EMG proles across steps with peaks occurring just before or at
the beginning of the swing phase, when ankle
exion is most needed. However,
NMES+RTT resulted in concentration of EMG activation during the initial swing
phase more than RTT only, as indicated by the larger increases in
. The ability
of the NMES+RTT therapy to shape the EMG patterns of the TA during stepping
were further demonstrated by changes in the Gaussian t parameters; however, it
appears that RTT alone can in
uence the EMG prole as much as NMES+RTT.
The EMG peak grew sharper, as measured by decreasing values. decreased
toward 0, indicating that the center of the peak moved closer to toe-o, or the
beginning of the swing phase; however, in Group 1 rats, the average center of the
peak returned to near the baseline value. We have seen this trend for kinematics,
34
such as step length (results not presented in this thesis), in which improvement
was observed in the rst 2 weeks of training followed by a regression to baseline
levels after switching to the 2
nd
therapy. It is possible that when the therapy is
benecial to motor learning, discontinuing the therapy and furthermore, switching
to a new therapy can disrupt that motor learning, thereby causing a regression in
performance. The eect of NMES+RTT and RTT alone on EMG proles were
compared when the robotic assistance was provided at gradually decreasing lev-
els such that the rat had more control over their own stepping and lesser forces
were imposed to allow for greater
exibility in the actual trajectory as training
progressed. In this case, both NMES+RTT and RTT appeared to be benecial
in organizing EMG activation patterns during step cycles, but it was not clear
whether NMES+RTT further increased the benet. It appears that NMES timed
appropriately to hindlimb stepping is at least as benecial as treadmill training, but
perhaps our stimulation protocol needs to be ne-tuned in order to reinforce the
motor learning that is induced by aerent activity generated by treadmill training.
5.2 Future Development
The NMES+RTT system development we have achieved so far have laid the
grounds for future research to comprehend how the underlying mechanism of the
observed eects. Thus far, we tested our hypothesis in a therapy which stim-
ulates the TA muscle alone. We plan for future development to include other
muscles besides TA which are involved in stepping (e.g., ankle extensor, hip exten-
sor and hip
exor muscles). Other challenges which remains outstanding include
whether the stimulation could be timed dierently or applied at dierent ampli-
tudes, pulse width, and frequencies to further improve the eects of NMES+RTT.
The NMES+RTT system that we are developing is designed for application in a
35
rodent model of spinal cord injury. This will allow us to perform several studies in
the future to assess the long-term eect of this NMES+RTT therapy. The results
presented here provide us with an impetus toward further developing our NMES
therapy to tap into spinal plasticity as a way of generating lasting rehabilitative
eects following spinal cord injury.
36
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Abstract (if available)

Abstract Neuromuscular electrical stimulation (NMES) has been used as a therapeutic tool for patients of neuromotor dysfunction to effectively regain some motor functions. It achieves this restoration of function by causing muscle contractions by applying electrical impulses to peripheral nerves. ❧ We have developed an NMES system for a rodent model of spinal cord injury (SCI) with the long term goal of creating a therapy which restores control over stepping back to the spinal circuitry. The therapy times NMES applied to the tibialis anterior (TA) ankle flexor muscle at the initial portion of the swing phase during robotic treadmill training (RTT) in an attempt to reinforce afferent activity generated just during treadmill stepping. ❧ Two studies were conducted to evaluate our proposed NMES+RTT therapy. In the first study, we compared the changes in electromyographic (EMG) activity of spinally contused rats who received NMES timed to the afferent feedback generated during robotic treadmill training (RTT) with rats receiving patterned NMES but randomly timed with respect to their hindlimb movements. The results indicated that stimulation appropriately timed to robotically treadmill training reshaped the EMG profile such that the EMG energy was concentrated during the initial portion of the swing phase, the same portion of the gait cycle during which stimulation was applied during training

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Asset Metadata

Creator Askari, Sina (author)

Core Title Electromyography of spinal cord injured rodents trained by neuromuscular electrical stimulation timed to robotic treadmill training

School Viterbi School of Engineering

Degree Master of Science

Degree Program Biomedical Engineering

Publication Date 07/26/2012

Defense Date 08/01/2012

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag EMG processing and applications,motor neuroprostheses,neuromuscular stimulation,neuromuscular systems,OAI-PMH Harvest

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Grzywacz, Norberto M. (committee chair), Won, Deborah S. (committee chair), Loeb, Gerald E. (committee member), Weiland, James D. (committee member)

Creator Email saskari@usc.edu,sina.askari@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c3-67091

Unique identifier UC11290015

Identifier usctheses-c3-67091 (legacy record id)

Legacy Identifier etd-AskariSina-1011.pdf

Dmrecord 67091

Document Type Thesis

Rights Askari, Sina

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the a...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA