Skeletal Muscle Plasticity As An Indicator of Functional Performance Post-Stroke
Phase: PHASE2
Conditions: Stroke
Sponsor: VA Office of Research and Development

O0844-R 
NCT01970592 
 
Skeletal Muscle Plasticity As An Indicator of Functional Performance 
Post-Stroke 
 
July 14, 2011 

Lower extremity power and locomotor function after stroke      1 
 
 
PI Name:   
Chris Gregory, PhD, PT:  PI 
 
 
Aaron Embry, DPT, MSCR: Investigator 
 
 
Patrick Morgan, MS: Coordinator 
 
Study Title:   Lower extremity power and locomotor function after stroke. 
TABLE OF CONTENTS  
 
Specific Aims                                
p. 1 
Background and Significance       
p. 2 
Preliminary Studies                       p. 2 
Research Design and Methods    
p. 4 
Protection of Human Subjects      
p. 9 
References                                   
p. 13 
Consultants                                  
p. 14 
Resources                                    
p. 14 
Investigator Brochure                   
p. 15 
Appendix                                      
p. 15 
 
 
A. 
SPECIFIC AIMS 
Post-stroke motor control is characterized by greatly reduced muscle power generation.  To date, 
it has yet to be established the extent to which muscle power limits walking performance or 
whether its remediation should be a primary component of locomotor rehabilitation.  The potential 
efficacy of increasing muscle power is suggested by studies showing that its reduction, compared 
to other impairment level measures, is more strongly associated with risk of falls and slow gait 
speeds.  In fact, impaired muscle power generation is the single strongest predictor of functional 
disability in an aging population. Further, while basic training to increase muscle strength (one 
component of power) has produced equivocal results, substantial evidence suggests that 
appropriately designed training can have potent effects on walking in those for whom it is 
appropriate. 
The major hurdle preventing understanding of how muscle power generation contributes to 
functional walking ability after stroke, and thus the efficacy of its rehabilitation, is the lack of a 
theoretical framework that defines and measures the complex multifactorial relationships between 
neural activation, muscle force generation and functional task performance. Impaired neural 
activation of a muscle group is differentially related to walking performance depending on 
activation magnitude, independence of activation at the appropriate time in the gait cycle, leg 
kinematics during activation and overall coordination of other walking tasks by different muscle 
groups. To gain a better understanding of this complex interaction, we have developed a 
comprehensive theoretical framework that defines and measures relevant neural and muscular 
factors that contribute to walking function in order to control for potential confounds in determining 
intervention efficacy.  We will apply this framework to Post-stroke Optimization of Walking 
using Explosive Resistance (POWER) training, a multi-joint, high-velocity resistance training 
paradigm that includes task-specific elements and individually targets muscle power dysfunction. 
We are uniquely well-suited to perform this work because we a) have developed key coordination 
measures on which the theoretical framework is based; b) have unique equipment to perform the 
novel intervention and c) have the imaging expertise to apply cutting-edge techniques for the first 
time in the stroke population. Through the use of our theoretical framework we will be able to 
explain for the first time why people did or did not respond and provide evidence establishing the 
Medical University of South Carolina Protocol 

Lower extremity power and locomotor function after stroke      2 
 
characteristics of those most likely to benefit (or not) from training.  As such, we propose the 
following aims over a four-year period: 
Aim 1: Determine the presence and magnitude of neural and muscular adaptations post-
stroke as predictors of impaired muscle power generation. We will measure pre-training 
muscle function parameters (strength & power) as well as neural (central activation & muscle 
coordination) and muscular (morphology & in-vivo bioenergetics) adaptations in the paretic and 
non-paretic legs of 28 persons with chronic hemiparesis (vs. matched controls). We will use 3-
dimensional magnetic resonance (MR) imaging to assess individual muscle cross-sectional area 
as well as 31P-MR spectroscopy to measure in-vivo muscle oxidative capacity and resting 
concentrations of inorganic phosphate. 
Aim 2: Quantify the effects of POWER training on the presence and magnitude of neural 
and muscular adaptations. POWER training consists of high-velocity resistive exercises that 
independently target the paretic and non-paretic limbs and will utilize a ZeroGTM overground body-
weight support (BWS) system to facilitate progressive loading and safe practice. Training also 
includes trials of fast overground walking (≥125% self-selected speed) with minimal BWS (or 
added mass as appropriate) to emphasize lower extremity power generation during walking as 
well as self-selected overground walking for task-specific practice.        
Aim 3: Establish the relationship between neural and muscular adaptations, lower 
extremity power generation and functional (locomotor) improvements following POWER 
training. To determine the most relevant predictors of functional recovery we will measure neural 
and muscular contributors to muscle power generation, complete a battery of clinical and 
functional assessments, and perform full biomechanical analyses of walking at four times (at 0, 4 
& 8 weeks of training and 8 weeks after training). Secondarily, we will associate changes in self-
selected walking speed, muscle coordination and power generation during walking to our 
historical cohort following task-specific locomotor training (VA RR&D B3983). 
B. 
BACKGROUND AND SIGNIFICANCE 
Stroke is the leading cause of long-term disability in the United States, affecting approximately 
795,000 people each year, with a surviving cohort of nearly 6.5 million (Lloyd-Jones et al., 2009). 
Seventy-three percent of those surviving stroke will have some degree of long term disability 
(Gresham, Duncan et al. 1995), and less than 50% of survivors progress to independent 
community ambulation (Perry, Garrett et al. 1995). Even among those who do achieve 
independent ambulation, significant residual deficits persist in balance and gait speed, with 60% 
of persons post-stroke reporting limitations in mobility related to walking (Perry, Garrett et al. 
1995).   
Hemiparesis, strictly defined as a muscular weakness or partial paralysis of half of the body, is 
seen in three-quarters of patients post-stroke. A primary disability associated with post-stroke 
hemiparesis is the failure to make rapid graded adjustment of muscle force within the context of 
purposeful complex movement patterns, such as are required during walking (i.e. muscle power). 
In walking, a primary impairment is a reduced ability to sufficiently activate muscles (Mulroy, 
Gronley et al. 2003).  Since improving walking is the most often stated goal of patients following 
a stroke (Bohannon, Andrews et al. 1988), interventions aimed at improving functional walking 
status, are critical for improving quality of life for hemiparetic individuals and their caregivers. 
Currently there are not established answers as to what extent muscle power generation deficits 
limit walking performance and whether their remediation should be a primary component of 
locomotor rehabilitation. We believe that much uncertainty arises from the complex multifactorial 
relationships between muscle force generation, neural activation and task performance.  To 

Lower extremity power and locomotor function after stroke      3 
 
distinguish among these, we have developed the first comprehensive theoretical framework that 
defines and measures these different factors in order to control for potential confounds and to 
identify the neurological, biomechanical and biochemical reasons an intervention was successful 
or not.   
Theoretical framework: Relationship between neural activation and task performance: The 
theoretical framework underlying the importance of impaired neural activation for walking 
performance is straightforward: acceleration of the mass of the body (or individual body 
segments) requires adequate force generation by the appropriate skeletal muscles coordinated 
to be produced at the appropriate time in the gait cycle. Impaired neural activation thus consists 
of two separate components: decreased neural activation magnitude (muscle weakness) and 
impaired neural activation coordination (independent muscle coordination), which is the ability to 
independently activate (not necessarily by itself, but with its usual synergists) a muscle at the 
appropriate time in the gait cycle. In addition, the specific muscle force generation patterns 
resulting from neural activation deficits will also differentially affect walking performance (e.g., 
speed) depending on the kinematic state of the leg at the time of activation and the overall 
coordination of other walking functions by different muscle groups (e.g., plantar flexor strength 
increases might not improve walking speed if a different muscle group is the weak link). Figure 1 
provides an example specific to the plantar flexor muscle group how the different factors can 
influence walking performance and the measurements we will make to assess the influence of 
each factor. 
 
Figure 1: Theoretical framework of complex multifactorial relationships between neural activation, 
muscle force generation and task performance. Illustrated are examples of how task performance can be 
limited by the plantar flexor (PF) muscle performance relative to each factor and how we will measure each 
factor. ICP refers to “Independent Co-activation Pattern” as identified by factor analysis from EMG data. 
Impaired neural activation magnitude (strength and power): Hemiparesis, strictly defined as 
(muscular) weakness affecting one side of the body, is seen in three-quarters of individuals 
following stroke. Weakness in this population results from both neural and muscular factors which 
include, respectively, the ability of the central nervous system to activate skeletal muscle as well 
as the force generating capacity of the muscle. Given the nature of neurological insult, the 
prevailing notion is that neural factors (i.e., central activation) are predominately responsible for 
weakness post-stroke. However, more recent studies confirm muscle atrophy as contributing 
mechanism underlying hemiparetic weakness and studies in clinical populations other than stroke 
suggest that in-vivo bioenergetic properties of skeletal muscle also contribute to weakness and 
explain strength deficits not accounted for by changes in muscle size and central activation. To 
date, the influence of these factors on hemiparetic weakness has not been explored.  
Neural Activation 
Magnitude
Strength: If PF cannot activate at 
sufficient magnitude then 
performance is limited, or, If PF 
can already activate at sufficient 
magnitude then further 
strengthening does not benefit  
performance (peak force)
Power: If PF cannot generate 
sufficient force in available time 
of gait cycle then performance 
limited (peak power)
Neural Activation 
Coordination
Independence: If PF are 
contained in an ICP with muscles 
usually in other ICP's then 
performance is limited (other 
muscles counteract  effects of 
PF's)
Muscle timing: If PF is on at 
inappropriate time (initial double 
support) or is not on at 
appropriate time (second half of 
stance) then performance is 
limited (% PF activity during 
specified gait region)
Muscle Force 
Generation
Kinematic state: If foot not 
behind center of mass in late 
stance then PF force generation 
will not accelerate the body 
forward (Leg angle)
Overall coordination: If other 
walking functions not sufficiently 
performed by other ICP's then 
performance limited (ICP #)

Lower extremity power and locomotor function after stroke      4 
 
Central activation: It is widely accepted that hemiparetic weakness results primarily from reduced 
central (cortical) activation of agonist muscles. Evidence of reduced central activation has been 
reported in the knee extensor muscles both during the early time period following stroke (i.e., first 
six months) as well as in subjects with more chronic injuries, indicating early and persistent 
bilateral disruption in the ability to volitionally activate skeletal muscle. Impaired central activation 
in these studies was greater in paretic vs. non-paretic muscles, yet could not completely explain 
the magnitude of weakness in either leg (Miller et al.;2009). Using a combination of superimposed 
electrical stimulation and surface electromyography (EMG), Klein et al. concluded that weakness 
of the plantar flexor muscle group in chronic stroke subjects mostly reflects central activation 
impairments, with small, but significant, contributions from muscle atrophy. Reduced muscle 
activity, indicated by diminished amplitude of EMG activity, is also indicative of impaired central 
activation and generally observed in paretic muscle during isolated joint strength testing as well 
as during functional movements (e.g. walking or reaching), with the extent of central activation 
impairment associated with functional disability.  A “saturation” of EMG activity, reflected by an 
absence of modulation in response to increased task demands, is also a common phenomenon 
following stroke and further supports reduced central activation as a primary contributor to post-
stroke muscle weakness. Despite reports of strong associations between impaired central 
activation, reductions in muscle strength and reduced functional performance, definitive evidence 
regarding the relationship between these outcomes is lacking because of the paucity of studies 
that simultaneously assess these and other variables that contribute to hemiparetic weakness. In 
the absence of studies quantifying central activation, muscle atrophy and other factors 
concurrently, the relative contributions of neural and muscular factors to hemiparetic weakness 
and the ensuing functional limitations remains largely unknown.   
Muscle atrophy: The loss of skeletal muscle mass (i.e. atrophy) following stroke has negative 
implications for strength and functional performance and may also have significant health-related 
consequences. Although it is well established that inactivity or disuse results in muscle atrophy, 
early studies provide conflicting results regarding the magnitude of muscle atrophy post-stroke. 
Reports of muscle atrophy (Jorgensen et al, 2001; Metok et al, 2003; Ryan et al, 2002) are 
countered by evidence of preserved muscle mass at both the whole muscle (Hachisuka, 2007; 
Carin-Levy et al., 2006) as well the individual fiber level (Slager et al., 1985). Such conflicting data 
led Patten and Pak (2008) to conclude that there is limited evidence to either support or refute 
the incidence and severity of muscle atrophy following stroke. These authors do, however, point 
out that more recent studies afforded the use of high-resolution imaging techniques (as proposed 
herein) offer considerably more support for muscle atrophy as a mechanism underlying 
hemiparetic weakness, though its importance in explaining strength deficits (or recovery) is 
unknown.  More recently, English et al. (2010) concluded that persons post-stroke have 
significantly less regional muscle mass than neurologically healthy individuals as well as in the 
paretic versus the non-paretic thigh, with reductions in thigh muscle mass measured using both 
magnetic resonance imaging (MRI) and computed tomography (CT).  Interestingly, the extent of 
paretic muscle atrophy (as opposed to weakness) correlates strongly with gait speed and reduced 
fitness in individuals following chronic stroke (Ryan et al.), though the lack of available knowledge 
regarding changes in muscle mass and their relationship to weakness and function represents a 
significant deficiency in the scientific literature that must be addressed.  
In-vivo bioenergetics: In addition to central activation and muscle atrophy, in-vivo bioenergetic 
properties of skeletal muscle can play a significant role in the development of muscle dysfunction. 
Specifically, an increase in inorganic phosphate concentration [Pi] measured using 31-
phosphorous magnetic resonance spectroscopy (31P-MRS) is predictive of decrements in muscle 
function, both in-vitro and in-vivo.  Increased [Pi] reduces calcium sensitivity in muscle and results 
in a rightward shift in the [Ca++]/tension curve, thus requiring greater calcium release to activate 
skeletal muscle. Increase in [Pi] has been observed in a variety of disorders including primary 

Lower extremity power and locomotor function after stroke      5 
 
mitochondrial diseases, myopathies, muscle injury, cast immobilization and denervation, 
(McCully, Kent et al. 1988; Argov and Arnold 2000; Tartaglia, Chen et al. 2000; Pathare, Walter 
et al. 2005; Pathare, Vandenborne et al. 2007) while reductions in [Pi] correlate with functional 
improvements following rehabilitation. In addition to changes in [Pi], 31P-MRS data have been 
utilized to identify abnormalities in skeletal muscle oxidative capacity, reflected by the rate of 
phosphocreatine (PCr) recovery following exercise, in various patient populations (Rossi and 
Lortet, 1996; Yoshida et al, 2001) as well as with normal aging  (Waters et al, 2003). PCr recovery 
rates have been extensively used in both healthy and diseased muscles as estimates of muscle 
oxidative capacity (Meyer 1988; Paganini, Foley et al. 1997; McCully, Mancini et al. 1999) and 
findings from these studies suggest that recovery of function is directly related to the increases in 
muscle oxidative capacity (Yoshida et al, 2001). To our knowledge there are no published data 
available that provide information describing in-vivo bioenergetics properties of muscle following 
stroke.  
Muscle power: Muscle power involves both strength and velocity components, and is determined 
by the force generating capacity of the muscle as well as its speed of shortening. Although the 
loss of muscle mass as well as the inability to activate muscle clearly contribute to the loss of 
muscle strength (and consequently power), these variables alone cannot account for the 
proportionally greater loss of muscle power than strength following stroke (Clark et al, 2006). 
Pronounced velocity dependent muscular deficits are present post-stroke and, in combination 
with substantial muscle weakness, significantly impact power generation when compared to 
neurologically healthy aged counterparts (Pohl et al, 2002; Clark et al, 2006). To a greater extent 
than muscle strength, muscle power is a significant predictor of functional ability and direct 
comparisons of power and strength demonstrate that muscle power consistently describes more 
of the variance in functional ability in mobility-limited elders (Bean et al, 2002). Deficits in lower 
extremity power generation are associated with increased levels of dependence, greater risk of 
falls and decreased walking speeds, (Bean et al, 2003; Chan et al, 2007; Kuo et al, 2006) though 
the relative importance of the various contributors to (reductions in) power generation post-stroke 
are largely unexplored. Our focus in this proposal is on the (in)ability of post-stroke muscle to 
generate power both in and away from functional task performance and to determine the effects 
of a novel intervention targeting lower extremity power generation in both the paretic and non-
paretic legs on functional (locomotor) recovery.     
Impaired neural activation coordination: What has often been incompletely addressed in 
previous research examining the role of weakness in impaired hemiparetic walking is the 
difference between what a muscle is capable of producing in a strength/power test (usually an 
isolated voluntary movement) and what it actually produces during the task of walking. Key issues 
to address are: 1) is voluntary strength/coordination representative of that during walking; and 2) 
can the muscle group being assessed/strengthened be independently activated during walking 
and is it being activated with the appropriate timing?  
Walking specific activation: In spinal cord injured subjects it has been shown that the muscle 
activation during voluntary testing is much reduced relative to that in walking (Maegele et al, 
2002). We (SK) have shown that evaluation using the Fugl-Meyer assessment, based on 
voluntary movement items meant to test independence from abnormal synergies, more poorly 
predicts walking function than does a prediction based on a factor analysis that determines 
independence from abnormal synergies during walking (Bowden et al., 2010). Thus, it is clear 
that voluntary strength testing outside of the context of walking may result in different force 
generation than seen during walking. We propose to make detailed biomechanical measures 
during walking to in part control for this issue.  
Independent muscle coordination: It is well understood that if there is increased activity in an 
antagonistic muscle group then the net joint moment associated with the target muscle output is 

Lower extremity power and locomotor function after stroke      6 
 
reduced. However, it is typically not considered that activity in muscles other than the classical 
antagonists can also reduce the output of the target muscles. Forward dynamical modeling has 
revealed the counterintuitive finding that muscles can accelerate all joints, even those that are not 
directly spanned by the muscle (Zajac et al 2002 & 2003). Using the example of the plantar flexor 
group (PF), we (SK) have shown that a primary function of the PF during walking is to accelerate 
the trunk forward in late stance (Neptune 2001). We have also shown that activity in the vasti 
group, rectus femoris, and hamstrings can impede forward trunk acceleration during the same 
gait cycle period (Neptune et al., 2004). We (SK) have also shown that the PF are often co-
activated with the vasti group, rectus femoris, and hamstrings in walking by more severely 
affected hemiparetic subjects (e.g., those with merged modules in Clark et al., 2010). An 
inescapable consequence of lost independence of the PF is that the effective trunk forward 
acceleration that would have occurred due to PF alone will be reduced due to the net backward 
trunk acceleration induced by the other coactive muscles. Thus, a substantial strength gain in PF 
may not have the desired effect on trunk acceleration if the subject co-activates the other muscles 
whenever they activate PF. Additionally, activity usually must occur at the proper time or else it 
can have a negative effect. Again using the example of the PF, activity during the initial double 
support phase (i.e. before PF is typically activated in healthy walking) actually acts to accelerate 
the trunk backward (Neptune 2001). Thus, the common complete stance phase co-activation 
pattern of PF with the uniarticular extensors and the hamstrings found by Clark et al. (2010) in 
the most impaired hemiparetic subjects would result in increased forward deceleration of the trunk 
in initial double support and decreased forward acceleration of the trunk in late stance as the 
positive PF effect is countered by the negative effect of the other coactive muscles. Note that 
increasing the PF activation (e.g., strengthening) in a subject locked in this co-activation pattern 
could even result in slower walking speed if the negative effects outweighed the positive effects. 
Influence of individual muscle force generation on walking performance: A final often 
unappreciated aspect of the influence of muscle force production on walking performance is that 
it is dependent on the kinematic state of the leg (e.g., Zajac et al 2002 & 2003). For example, we 
(SK) have shown that the extension of the paretic leg in terminal stance is strongly related to the 
propulsion generated (Peterson et al., 2010). This can be particularly problematic in subjects with 
a “step-to” gait who do not advance the non-paretic leg beyond the paretic leg during non-paretic 
step. As a result the paretic leg may not extend beyond the trunk center of mass and PF force 
generation can act to raise the body center of mass instead of accelerating the trunk forward as 
would be the result if the leg were in its usual kinematic state. Again, note that increasing the PF 
activation (e.g., strengthening) in a subject with this type of kinematic pattern would not be 
expected to increase speed as the trunk would not be accelerated forward by the increased PF 
force generation. 
Importance of plantar flexor function: Hemiparetic walking is associated with a reduced ability 
to generate sufficient muscle power, especially within a critical temporal window to execute the 
transient motor events encountered during the gait cycle. We posit that locomotor ability following 
stroke is causally related to a person’s success at producing sufficient muscle power (with the 
ankle plantar flexor muscle group having a primary role) to meet the task demands of bipedal 
walking. Recent studies have demonstrated the importance of the ankle plantar flexor power 
generation to locomotor ability, (Kim et al., 2003) with deficits in plantar flexor function reported 
to explain 67 to 72% of the variance in walking speeds post-stroke (Nadeau et al., 1999; Neptune 
et al., 2005). Decreased power generation means that the necessary mechanical energy for the 
trunk and legs may not be available, thereby negatively impacting walking performance (e.g. trunk 
forward progression and ipsilateral swing initiation) and decreasing functional independence 
(Mulroy et al., 2003; Chen et al., 2008). By training using a program designed to positively affect 

Lower extremity power and locomotor function after stroke      7 
 
muscle power generation, we aim to effectively attenuate impaired power generation, thereby 
improving locomotor ability post-stroke.  
Impact of training on hemiparetic muscle function: Hemiparetic muscle weakness is a 
significant predictor of lower and upper extremity motor recovery in both acute and chronic stroke 
subjects (Sharp & Brouwer, 1997; Patten et al., 2003; Northrop et al., 2003). Given this observed 
relationship, it would seem logical to intervene by strengthening weak muscle groups. However, 
evidence regarding the efficacy of interventions aimed at attenuating muscle weakness and the 
ensuing functional consequences in the post-stroke population is equivocal and viable therapeutic 
options to remediate hemiparetic muscle weakness remain a pressing challenge.  
Progressive resistance training is widely accepted as the most effective method for developing 
muscular strength and is currently prescribed by most major health organizations for improving 
health and fitness (National Institute on Aging, 1999). Resistance training is shown to improve 
lower extremity strength following stroke and, when delivered at appropriate intensities, can 
provide significant functional benefit (Teixeira-Salmela, 1999; Lee et al, 2010).  A recent 
quantitative review,(Dickstein, 2008) concluded that even though prevailing clinical thought 
argues that functional improvements emerge only from task-specific training, measurable gains 
in lower extremity strength following resistance training are associated with functional 
improvements in the post-stroke population. It should be noted that studies describing functional 
outcomes following strengthening in the post-stroke population are historically equivocal, though 
consistency with regards to intensity of the intervention in recent studies supports the argument 
for strengthening this cohort.  A unique aspect of the proposed training is the focus on high-
velocity concentric and eccentric contractions, a characteristic seemingly most appropriate for 
targeting post-stroke muscular dysfunction (Clark et al, 2006). Interventions targeting muscle 
power (i.e. training at high-velocities) in the aged result in similar increases in muscle strength 
compared to slow velocity training, yet elicit an over two-fold greater improvement in peak power. 
The high-velocity component is critical to elicit these responses, as losses in muscle power with 
aging (as well as neurological injury) appear to be due to greater declines in the velocity rather 
than the force component of muscle power production (Fielding et al, 2002; Bean et al, 2004). In 
fact, recent studies have shown that muscle power explained more of the variability in functional 
performance than maximal strength (Bean et al, 2002).  
Design of viable therapeutic options targeting hemiparetic muscle dysfunction and the ensuing 
functional consequences remains a pressing challenge for biomedical research, and is contingent 
upon reliable information describing the functional significance of target muscle(s) as well as the 
most important neural and muscular characteristics to address to maximize functional gains. Our 
long-term goal is to develop rehabilitation therapies that maximize improvements by addressing 
the physiological mechanisms that limit functional performance in each individual, thereby 
reducing disability and improving quality of life following stroke. 
 
C. 
PRELIMINARY STUDIES 
We believe that a theoretical framework based on the underlying causative mechanisms 
contributing to limitations in functional walking performance offers the greatest potential to 
develop best practice for walking recovery. Our proposal is based on the assertions that: 1) the 
ability to generate sufficient lower extremity muscle power is impaired and is in large part 
responsible for functional disabilities following stroke and 2) the proposed training protocol 
effectively attenuates impaired muscle power generation and improves locomotor function.  These 
beliefs were developed based on findings from our preliminary studies as well as the studies of 
others.  The following section outlines work to date quantifying adaptations in lower extremity 
skeletal muscle in the paretic and non-paretic legs that are known contributors to weakness and 
impaired locomotor function.  In addition, we demonstrate preliminary support for the use of a 

Lower extremity power and locomotor function after stroke      8 
 
novel rehabilitation program herein referred to as Post-stroke Optimization of Walking using 
Explosive Resistance (POWER) training. 
Mechanisms underlying deficits in muscle power generation: The impaired neural activation 
that characterizes hemiparesis results in a functional muscle weakness during walking as muscles 
often cannot generate sufficient force in the required amount of time. This rate dependent deficit 
is characterized by the reduced muscle power generation ability that is the focus of the proposed 
study. Muscle weakness is arguably the most prominent motor deficit in the post-stroke population 
and is strongly correlated with decreased functional abilities, including reduced gait speeds. To 
date, the relative importance of the various factors that contribute to muscle weakness (and 
subsequently to muscle power generation) in this population have not be adequately described. 
The following preliminary studies highlight significant reductions in muscle peak torque generation 
about the ankle and knee joints that is associated with reductions in muscle cross-sectional area 
(CSA) as well as the inability to voluntarily activate muscles in persons post-stroke. We also 
demonstrate preliminary findings suggesting that inorganic phosphate concentration [Pi] is 
elevated, a characteristic known to inhibit force production in-vitro and in-vivo following periods of 
disuse. 
Muscle strength and power deficits are significant post-stroke: Figure 2 illustrates deficits in 
the ability to generate peak torque in the plantar flexor and knee extensor muscle groups in a 
group of subjects post-stroke (n=7 with moderate to severe motor impairments), relative to 
matched (gender, age, height and weight) neurologically healthy individuals. Specifically, peak 
torque production in the paretic and non-paretic muscles was 76% and 62% lower in the plantar 
flexors and 78% and 61% lower in the knee extensor muscle group, respectively. In addition, the 
average rate of torque development (ARTD), defined as the time integral necessary to generate 
from 20 to 80% of peak torque, was significantly reduced in person’s post-stroke (~89% and 78% 
in paretic and non-paretic muscle, respectively), indicative of substantial deficits in muscle power 
generation in these muscle groups. Deficits in torque production in our subjects were associated 
with reduced voluntary activation in both the knee extensor and plantar flexor muscle groups 
(Figure 2).  Central activation impairment is only ~5% in neurologically healthy individuals, 
whereas paretic central activation impairments are 66% and 64%; and non-paretic activation 
impairments are 40% and 52%; in the KE and PF muscle groups, respectively.  Collectively, our 
data demonstrate significant muscle force generation dysfunction in both paretic and non-paretic 
limbs that is partially explained by reduced central activation of these muscles following stroke. 
 
 
 
Figure 2: Peak torque and voluntary activation deficits in paretic (black bars), 
non-paretic (white bars) and control (grey bars) PF and KE muscle groups 

Lower extremity power and locomotor function after stroke      9 
 
Muscle morphology post-stroke: We collected 
MRI data from 17 hemiparetic subjects (6-60 
months post-stroke) as well as from matched 
(gender, age, height and weight) controls. 
Individual muscle cross-sectional area (CSA) 
was measured in plantar flexor (soleus, med. & 
lat. gastroc), dorsi-flexor (tibialis anterior) and the 
quadriceps femoris muscle group (Figure 3). 
Muscle atrophy is defined as the % difference 
between control and hemiparetic limbs. Our data 
show a reduction in CSA following stroke that is 
muscle group dependent.  Specifically, CSA was 
reduced in the paretic and non-paretic medial 
gastrocnemius 
(27% 
& 
9%), 
lateral 
gastrocnemius (16% & 6%) and soleus 20% & 13%). Quadriceps muscle CSA was reduced 24% 
and 5% while the TA was 9% and 17% smaller in paretic and non-paretic muscle, respectively.  
In-vivo bioenergetics are altered and associated with 
muscle dysfunction post-stroke: We collected localized 
31P-MRS data at rest from the paretic and non-paretic limb 
from eight post-stroke participants as well as from the 
dominant limb of 8 neurologically healthy individuals 
matched on the basis of age, gender, height and weight. 
Data were acquired with a total averaging time of 5 minutes 
and a TR = 5 sec.  Marked differences were found in resting 
[Pi] levels between the paretic limb and the control limb (5.43 
vs. 3.01 mM Pi) as well as between the paretic and non-
paretic limbs (5.43 vs. 4.46 mM Pi; Figure 4).  These data 
demonstrate experience acquiring 31P-MRS data in muscle 
from individuals post-stroke. In addition, the findings provide 
support for the contribution of in-vivo bioenergetics 
properties to be affected following stroke and negatively impact muscle function in this population. 
Summary: The consequences of alterations in skeletal muscle post-stroke are far reaching and 
contribute to decreased motor control and overall fitness, development of functional limitations, 
and long term disability. We have highlighted several adaptive changes that occur that contribute 
to muscle dysfunction in persons post-stroke when compared to neurologically healthy 
individuals.  To date, however, the relative importance of these factors as well as whether and 
how these impairments relate to existing functional deficits is yet unknown. Furthermore, the 
extent to which these alterations are amenable to rehabilitation training and the degree to which 
changes in these properties relate to functional improvements would be valuable information to 
help guide therapeutic decision making in the treatment of post-stroke locomotor dysfunction. 
Plantar flexor muscle power generation is associated with locomotor function post-stroke: 
Individuals following stroke typically present with some degree of residual motor function. The 
extent of this residual function varies greatly from person to person, and significant locomotor 
impairments often persist. Although a number of factors likely contribute to slow walking, we 
examined the importance of muscle power generating capacity of the plantar flexor muscle group 
during dynamometric strength testing in predicting locomotor ability in individuals with chronic 
post-stroke hemiparesis (n=23). Ankle plantar flexor power was determined bilaterally. In addition, 
self-selected gait speed was measured during over-ground walking. Significant correlations were 
Figure 4: [Pi] in paretic, non-paretic and control 
PF muscles collected via 31P-MRS showing 
significant differences between legs (paretic > 
Figure 3: Relative differences in paretic (grey bar) and 
non-paretic (black bar) lower extremity muscles 
compared to controls. Dashed line represents average 

Lower extremity power and locomotor function after stroke      10 
 
found between self-selected gait speed and ankle power in the paretic (r = 0.78) and non-paretic 
(r = 0.46) legs (Figure 5).  The strength of the correlation between the paretic PF muscle group 
and gait speed suggests the importance of ankle power in predicting locomotor ability post-stroke 
and suggests paretic PF function as a potential target for improving locomotor ability in this large 
clinical cohort.  
 
Paretic ankle powers relate to locomotor performance: 
We measured ankle power in the paretic limb during walking 
at self-selected walking speed in hemiparetic subjects (n=21; 
gait speeds 0.2–1.0 m/s) as well as a control group at matched 
speeds (Figure 6). Significant reductions in ankle power 
generation are present in participants classified as having mild 
and moderate strokes. Reduced power generation was also 
evident across the hip and knee joints at matched speeds, 
though the most prominent deficits are in the ankle and 
strongly correlate to hemiparetic severity.  Additional data from 
this study of reveal that peak ankle power during walking in 
hemiparetic subjects (independent of severity) is highly 
correlated with self-selected walking velocities (r=0.77, 
p=0.0004), suggesting a significant functional relationship between paretic ankle power 
generation and gait speed post-stroke. 
 
 
 
 
Figure 6: Ankle power during walking 
following moderate (top) and mild 
(bottom) stroke. 
Figure 5: Correlations between self-selected gait speed and plantar flexor power in the paretic (left) and non-
paretic (right) legs. 

Lower extremity power and locomotor function after stroke      11 
 
Understanding muscle coordination through independent muscle co-activation patterns. 
We have established a basis for studying muscle co-activation patterns consistent with the 
concept that stroke limits the ability to activate certain muscles, or patterns of muscles, 
independent of a mass extension and flexion co-activation. In addition, recovery of mobility occurs 
when independent muscle activation is regained 
allowing 
the 
critical 
biomechanical 
functions 
associated with mobility to be better executed 
(published in J Neurophysiology; Clark et al, 2010). 
Analyzing EMG recordings from healthy individuals, 
we found that a small set of independently timed 
patterns (n=4) of muscle co-activation accounted for 
step-to-step variability of muscle activity in eight 
muscles over a wide range of walking speeds (Figure 
7). We hypothesized that the health of the locomotor 
control 
system 
depends 
on 
the 
number 
of 
independent co-activation patterns (ICPs) needed to 
account for the EMG signals. Indeed, we found that 
the muscle activity in many paretic legs could be 
accounted for with only two ICPs compared to control legs where four ICPs were needed (i.e., 
muscle activity was less independently controlled in the paretic legs; Figure 7). We further found 
that reduced ICPs was associated with poorer walking performance, including decreases in 
speed, step length asymmetry, propulsive force asymmetry and speed adaptability (Figure 8). 
 
Effective locomotor training is able to improve the quality and independence of co-
activation patterns. Two recent studies using rigorous quantitative EMG analysis have 
emphatically concluded that the recovery from acute stroke accompanying a non-locomotor-
specific rehabilitation protocol occurs without improvement in the timing of EMG activity (Den 
Otter, Geurts et al. 2006; Buurke, Nene et al. 2008).  In contrast, we find that improvement in 
timing does occur in recovery using a locomotor-specific training protocol.  We tested locomotor 
output before and after an intensive locomotor training program, consisting of 36 sessions over 
12 weeks.  Twenty-seven participants walked on a treadmill with the minimum amount of body 
weight support needed to allow for 20 total minutes of walking per session.  Using the same EMG 
analysis as in the previously mentioned studies we showed that EMG timing changes do occur. 
Figure 7: Number of ICP’s during walking in 
control and hemiparetic subjects. 
Figure 8: Locomotor output complexity 
(i.e., number of ICP’s) and walking 
performance assessed via overground 
self-selected walking speed (top left), 
speed difference between self-selected 
and fast walking (top right),  propulsive 
asymmetry (bottom left), and step length 
asymmetry 
(bottom 
right). 
Healthy 
control data are shown as a reference. 
The 3 horizontal bars representing each 
variable indicate, from bottom to top, the 
lower 
quartile, 
median, 
and 
upper 
quartile. Error bars indicate ±1.5 · 
interquartile range. Circles represent 
outlying data points. Low, moderate and 
high complexity represent two, three and 
four ICP’s, respectively. 

Lower extremity power and locomotor function after stroke      12 
 
We also demonstrated that the EMG changes were consistent with increased independence from 
a general stance-phase co-activation. The number of independent co-activation patterns needed 
to account for muscle activity of the paretic limb following locomotor training increased in fourteen 
of the nineteen participants who began with less than four patterns (nine subjects began with four 
patterns).  No participants experienced a reduction in the number of patterns. These findings 
strongly suggest that post-stroke locomotor training (cf., general neurodevelopment approach) 
improves muscle activation differentiation during walking and that this differentiation is crucial for 
improved walking. Of interest is whether POWER training will similarly improve muscle activation 
differentiation, or will provide different benefits that may be enhanced if combined with other 
training approaches. 
Subjects without ability to independently activate PF generate dramatically less propulsion 
with their paretic leg. Considering the hemiparetic subjects in our experimental study who had 
only three instead of four independent patterns: one subset, who merged the normal late stance 
pattern (e.g., soleus and gastrocnemius) with the normal early stance pattern (e.g., vastus 
medialis and gluteus medius), generated significantly less body forward propulsion with their 
paretic leg (mean = 73% less; Figure 9 left plot). However, another subset, who retained the 
independent late stance pattern (soleus and gastrocnemius) but instead merged the swing-to-
stance pattern (e.g., hamstrings) with the early stance pattern (vastus medialis and gluteus 
medius), generated only slightly reduced propulsion (~11% less; Figure 9 right plot).  
 
 
Effects of POWER training on persons post-
stroke: We recently completed data collections on 
five individuals (4 males; 62.4 ±7.3 yrs; 45.2 ± 25.7 
mos. post-stroke) who completed 24 sessions of 
POWER training. Training resulted in increases in 
self-selected and fastest comfortable walking 
speeds, improved walking endurance, as well as 
bilateral increases in muscle strength and power 
generation. Specifically, overground self-selected 
walking speed (SSWS) increased from 0.58 ± 
0.24 m/s to 0.78 ± 0.28 m/s following training. 
Similarly, fastest comfortable walking speed 
increased on average from 0.91 ± 0.32 m/s to 1.35 
Figure 9: Examples of A/P ground reaction forces in post-stroke subjects with merged early and late stance modules 
(left) and with merged swing-to-stance and early stance modules but independent late stance pattern (right).  
Figure 10: Bi-weekly gait speeds for individual 
subjects completing POWER training.   

Lower extremity power and locomotor function after stroke      13 
 
± 0.52 m/s.  Bi-weekly measures of SSWS 
suggest continuous improvements over the 8 
week period (Figure 10). Of note, the average 
increase in gait speed (i.e., 0.20 m/s) for our 
group (n=5) exceeds the clinically meaningful 
difference recently reported for participants in the 
recently completed LEAPS trial. Increases in gait 
speed 
for 
individual 
subjects 
were 
also 
accompanied by increases in paretic hip, knee 
and ankle joint powers.  Of note, peak paretic 
ankle power increased by an average of ~31% 
during walking at self-selected speed between 
the pre- and post-training time points. This 
increase is important as it provides evidence of 
carry-over from training-induced improvements in 
muscle power generation to task-specific performance (Individual subject power profiles shown 
in Figure 11). Non-paretic ankle power during decreased ~12%, suggesting that compensatory 
strategies at the ankle were not associated with behavioral improvements.  In addition to changes 
in gait speed, subjects realized average improvements in 6 minute walk test (6MWT) of (139.8 ± 
47.6 ft.), a change shown to be clinically important. 
In addition to improved walking speeds, peak muscle power generation during strength testing 
increased in the paretic and non-paretic plantar flexor (64.9% and 52.5%; Figure 12) and knee 
extensor (62.3% and 68.7%) muscles. Contributing to increases in muscle power, peak torque 
production increased in paretic and non-paretic plantar flexor (39.7% and 47.7%) and knee 
extensor (23.3% and 32.6%) muscle groups. In addition, greater plantar flexor peak velocity of 
contraction in paretic (154±39 º sec-1 pre vs. 237±55 º sec-1 post) and non-paretic (213±44 º sec-
1 pre; 306±69 º sec-1 post) legs as well as increases in paretic (12.8%) and non-paretic (9.1%) 
cross-sectional area also resulted from training. Similarly, increases in peak contractile velocity 
as well as muscle CSA and voluntary activation for the KE muscle group also resulted from 
training. 
 
D. 
RESEARCH DESIGN AND METHODS (including data analysis) 
Procedures Relative to Specific Aims: 
Aim 1: Determine the presence and magnitude of neural and muscular adaptations as 
Figure 11: Paretic ankle power profiles for 4 subjects 
at self-selected speed at pre (blue), 4 week (red), 6 
week (purple) and post (green) POWER training. 
Figure 12: Individual subject peak paretic plantar flexor muscle power generation during dynamometric evaluation 
(A) as well as during self-selected walking speed (B) at pre (black bars) and post (red bars) POWER training time 
points.  
A 
B 

Lower extremity power and locomotor function after stroke      14 
 
predictors of impaired muscle power generation in persons post-stroke. 
Rationale: Our preliminary data indicate a significant reduction in peak torque generation in the 
plantar flexor and knee extensor muscle groups relative to matched (gender, age, height and 
weight) controls.  In addition, reductions in muscle cross-sectional area (CSA) along with impaired 
central activation and altered in-vivo bioenergetic properties (e.g., increased [Pi]) are also 
characteristic of muscle post-stroke and likely contribute significantly to hemiparetic muscle 
dysfunction.  To date, the physiological mechanisms that contribute to hemiparetic muscle 
dysfunction are largely unstudied.  
Summary of Experiment & Research Design: We will perform comprehensive dynamometric, 
electrophysiological and magnetic resonance assessments of paretic and non-paretic 
musculature.  Measurements will be performed on a total of 28 subjects at least six months 
following stroke and comparisons made to the dominant leg of a group of matched (age, gender, 
height & weight) neurologically healthy individuals (n=28). In doing so, we will determine if, and 
to what extent, neural and muscular factors differ between legs (paretic vs. non-paretic vs. 
control).  In addition, we will determine the relationship between these factors and impaired 
muscle power generation. Our primary outcome measures in the ankle plantar flexor and knee 
extensor muscle groups will include 1) peak torque and power generation determined via 
isokinetic and isotonic dynamometry, respectively; 2) central activation measured using 
superimposed neuromuscular electrical stimulation; 3) muscle cross-sectional area (CSA) 
determined via MRI; and 4) muscle oxidative capacity (reflected by the rate of PCr recovery) and 
resting concentrations of inorganic phosphate [Pi] measured using 31P MR spectroscopy.  
Data Analysis Plan: The influence of neural and muscular adaptations (central activation, muscle 
CSA, in-vivo oxidative capacity and [Pi]) on peak power generation at baseline will be conducted 
using mixed effect regression models.  The mixed models will be used with random subject effects 
to account for the dependent nature of the data collected on paretic and non-paretic legs within 
the same individuals.  The baseline measure of peak power generation will serve as the 
dependent variable, with fixed effects for leg involvement (paretic vs. non-paretic) and for neural 
and muscular adaptation measures.  Model fit will be assessed via Akaike Information Criteria 
(AIC).  Partial correlations and standardized β coefficients will determine those factors with the 
strongest influence on muscle power generation.  The models will also allow us to address 
secondary questions such as the differences between peak power generation and neural and 
muscular adaptation measures in paretic and non-paretic limbs. 
Expectation: We hypothesize that the strongest predictor of impaired muscle power generation in 
the paretic and non-paretic legs will be central activation. Further, in-vivo oxidative capacity and 
[Pi] in both the paretic and non-paretic legs will be weakly associated with peak power generation, 
while CSA will only be significant in the paretic leg. We also expect significant reductions in paretic 
peak power generation, central activation, CSA and in-vivo oxidative capacity as well as an 
increase in [Pi], when compared to non-paretic and control legs.  Further, differences in peak 
power, central activation and [Pi], but not CSA, will be present between the non-paretic and control 
legs. 
Innovation: The proposed investigation combines contemporary, high resolution MR imaging and 
spectroscopic techniques concurrently with electrophysiological assessment of central activation 
impairment and dynamometric evaluations of muscle strength and power, which together will 
produce unequivocal evidence of the presence, magnitude and relative importance of neural and 
muscular factors as contributors to impaired hemiparetic muscle function.  
Aim 2: Quantify the effects of POWER training on the presence and magnitude of neural 
and muscular adaptations in paretic and non-paretic muscle post-stroke  

Lower extremity power and locomotor function after stroke      15 
 
Rationale: To date, the physiological mechanisms that contribute to improvements in lower 
extremity muscle power generation in hemiparetic subjects are largely unstudied.  Moreover, how 
these variables impact functional performance would provide a foundation for the development of 
effective rehabilitation interventions targeting functional recovery post-stroke. 
Summary of Experiment & Research Design: Twenty-eight subjects will participate in a novel 
training paradigm targeting lower extremity muscle function. Training will take place over an 8-
week period, three times per week on non-consecutive days. Exercises will be performed in the 
paretic and non-paretic limbs separately and progressed as tolerated across the 8-week period. 
Dynamometric evaluations of isokinetic strength and isotonic power will be performed prior to, 
after 4 and 8 weeks of training as well as 8 weeks following cessation of training (Figure 13). 
Assessments of muscle morphology (CSA) and in-vivo bioenergetics (PCr recovery and [Pi]) as 
well as full biomechanical assessments of walking will be performed at the same time points, 
allowing determination of the efficacy (and persistence) of training on the proposed outcomes. 
We will perform walking analysis over-ground and on the instrumented treadmill by collecting: (i) 
kinetics (3- dimensional ground 
reaction forces and moments), (ii) 
kinematics and iii) EMG from each 
leg. 
For 
each 
kinesiological 
measure, averages over the gait 
cycle 
for 
each 
leg 
will 
be 
calculated for each subject. Our 
primary outcome measures during 
biomechanical assessments will 
be peak ankle plantar flexion and knee extension power generation, with secondary variables of 
interest to include paretic step length ratio and paretic propulsion. A battery of clinical 
assessments to evaluate degree of function and disability will be performed prior to as well 
following training and at the 8 week post-training time point (see Procedures-Specific).   
Data Analysis Plan: To quantify the effects of our POWER training intervention on neural and 
muscular adaptations, we will utilize repeated measures mixed effects regression models to 
assess for significant changes in our outcomes over time.  Neural and muscular adaptations (on 
both the paretic and non-paretic legs) will serve as dependent variables in separate models, with 
time serving as the key independent variable in each. Various error structures associated with the 
repeated measures over time will be considered (e.g. compound symmetry vs. auto-regressive), 
and final error structures will be selected based on AIC values.  Having random subject effects in 
the models will account for correlation among measures within subjects over time.  Secondary 
analyses, incorporating differences in the paretic and non-paretic legs as dependent variables, 
will examine whether changes over time are more pronounced in the paretic vs. non-paretic leg. 
These models will also incorporate random subject effects to account for within-subject 
dependence.  Error correction will be set to maintain type one error at 5% with a desired power 
of 80%.   
Expectation: We hypothesize that POWER training will result in significant increases in muscle 
peak power generation, central activation, muscle CSA and in-vivo oxidative capacity as well as 
a concomitant decrease in [Pi].  Further, we expect changes in these variables will be greater in 
the paretic compared to the non-paretic leg. We also expect improvements in Clinical 
Assessments as a result of training as well as increases in our measures of locomotor function 
(see Procedures-Specific). 
Innovation: Through conduct of the proposed experiments, we will generate a rich data set, 
capable of relating measures of lower extremity power generation (both in and away from the task 
of walking) with functional walking performance. The proposed neuromuscular assessment 
Figure 13: Timeline for measures during POWER training

Lower extremity power and locomotor function after stroke      16 
 
techniques are state-of-the-art, and very few have even been applied to the post-stroke 
population, let alone used together to broadly assess changes in response to intervention. In 
addition, the unique biomechanical testing allows investigation of changes in steady-state bilateral 
walking, whereas most previous studies only evaluate the changes in outcomes (i.e., walking 
speed), with little (if any) information presented on changes in kinematics,  kinetics or muscle 
coordination. The successful completion of this study will provide an entirely new level of evidence 
for the functional changes resulting from a novel rehabilitation intervention and the resulting 
framework for mechanisms underlying the adaptations in walking could lead to a more integrative 
approach in the development of novel neurorehabilitation strategies (e.g. adjunctive therapies 
incorporating multiple training modalities to maximize recovery of function). If our hypotheses 
prove to be correct, the data will emphasize the importance of lower extremity power generation 
for improving hemiparetic walking and provide a foundation upon which further novel rehabilitative 
programs can be developed, including application to populations other than stroke who present 
with reduced muscle function and impaired walking (e.g. aging, SCI, TBI, PD, MS). 
Aim 3: Establish the relationship between neural and muscular adaptations, muscle power 
generation and functional (locomotor) improvements in persons post-stroke following 
POWER training.  
Rationale: Given that in persons post-stroke, improving walking is 1) independently related to 
overall health status; 2) a strong predictor of functional recovery and 3) the most often stated goal 
during rehabilitation, interventions aimed at improving functional walking status are critical to 
increasing independence and improving quality of life for patients and their caregivers The 
advanced methodologies proposed herein and the novel theoretical framework we have 
developed allow for detailed investigation of the neural and muscular factors that contribute to 
(changes in) muscle power generation. In addition, the state-of-the-art assessments of walking 
provide a comprehensive evaluation of locomotor behavior and the biomechanical mechanisms 
underlying hemiparetic walking performance. Moreover, we seek to identify the muscular 
characteristic(s) that best predict functional improvement and provide evidence establishing the 
characteristics of those most likely to benefit (or not) from training. 
Summary of Experiment & Research Design:  We will determine the relationship between 
changes in neural and muscular factors and improved power generation following training. We 
will also assess functional improvements via the proposed clinical assessments as well as through 
full biomechanical evaluations of walking.  
Data Analysis Plan: We will assess relationships for changes in central activation, muscle CSA 
and [Pi] (predictor variables) with improvements in muscle power generation (criterion variable) 
and self-selected walking speed by using mixed effects regression models, which, by 
incorporating random subject effects, will allow us to account for correlation of measures made 
on the same individual over time.  We will also use measures of muscle power generation in the 
paretic and non-paretic knee extensor and plantar flexor muscle groups as predictor variables in 
a multivariable linear regression model to assess relationships with self-selected walking speed. 
Standardized β coefficients from these regression models will help us determine which factors 
have the strongest influence on our outcome variables (i.e. power generation and self-selected 
gait speed). 
Secondary Questions: Although this proposal is not powered to examine differences in efficacy 
and mechanisms of response between POWER training and other intervention approaches (e.g., 
locomotor training), we intend to investigate these via exploratory post-hoc analyses to compare 
with an existing data set from a Locomotor Training trial in persons with chronic stroke (the same 
population we will be studying) recently completed by us (VA Merit Award B3983, Kautz PI). We 
will first compare the effect on self-selected and fastest comfortable walking speed for the two 

Lower extremity power and locomotor function after stroke      17 
 
interventions. Then we will conduct a detailed biomechanical assessment, from which we will 
calculate moments, powers, work, and kinematics, as well as the electromyography (EMG) data 
to measure muscle coordination. Although we do not present specific hypotheses related to 
differences between POWER training and the task-specific approach utilized in our previous trial, 
we believe this information will be extremely valuable in explaining the neural coordination 
associated with recovery of walking and provide insight on the emerging similarities and 
differences of these presumably distinct approaches to locomotor recovery.  Dr. Kautz has a 
proven track record of performing successful quantitative analyses from biomechanical 
assessments and will direct the interpretation of these data.  In addition, this proposal will leverage 
Dr. Kautz’ currently funded R-01, which has already developed the tools to analyze the 
coordination of EMG activity during multiple locomotor tasks in even greater detail. 
Expectation: We hypothesize that this type of training delivered separately to the paretic and non-
paretic legs will result in improved functional performance that is associated with increased lower 
extremity muscle power generation (primarily the paretic plantar flexors).  Further, we expect that 
post-hoc analyses of the characteristics of responders versus non-responders will be especially 
informative and will open the door for subsequent studies to study different adjunctive approaches 
to locomotor recovery. 
Innovation: Three novel components make this study highly innovative: 1) state of the art 
magnetic resonance and biomechanical assessments of in-vivo bioenergetics and neural deficits; 
2) development of a novel training intervention that includes task-specific components; and 3) a 
unique measure of the coordination of muscle activity to more fully quantify neural activation 
deficit (i.e., while activation deficit tells how completely the muscle is activated, our coordination 
measure tells whether the muscle can be independently activated at the appropriate point in the 
gait cycle). Detailed mechanistic studies, such as that proposed, allow for post-hoc analyses to 
determine for whom the intervention does and does not work, and can suggest why by providing 
scientific evidence of the underlying mechanisms contributing to post-stroke muscle dysfunction 
and, more importantly, how these mechanisms respond to therapeutic intervention. 
Procedures (Specific): 
Subjects: Subjects (male and female), ages 50-70, will be screened and recruited for the study 
6-24 months following stroke. We will limit inclusion to subjects within this age range following 
stroke in an effort to control for differences in muscle power generation, coordination as well as 
responses to training that may associated with the aging process. The pool of post-stroke 
candidates for the study will be recruited from inpatient rehabilitation programs at the Ralph H. 
Johnson VAMC (see Dr. Hinson letter of support) as well as the Medical University of South 
Carolina, Charleston, SC. All participants will have had a new ischemic stroke. Diagnosis will be 
confirmed by a positive CT or MRI performed during stroke admission but not part of these study 
procedures. Eligible participants will be screened for study participation and, if appropriate, 
accepted into the study. In addition, a group of neurologically healthy individuals matched on the 
basis of gender, age (± 5 years), height (± 5 cm) and weight (± 5 kg) will also be recruited. 
Inclusion criteria will be: 1) age 50-70, 2) stroke within the past 6 to 24 months, 3) residual 
paresis in the lower extremity (Fugl-Meyer LE motor score <34), 4) ability to walk without 
assistance and without an AFO on the treadmill ≥ 30 seconds at speeds ranging from 0.3 - 0.8 
m/s, and 5) provision of informed consent. In addition, all subjects who meet criteria for the training 
portion must complete an exercise tolerance test and be cleared for participation by the study 
cardiologist. Exclusion criteria will be: 1) Unable to ambulate at least 150 feet prior to stroke, or 
experienced intermittent claudication while walking; 2) rating on Modified Ashworth Scale ≥3 at 
the knee or ankle; 3) limited lower extremity range of motion of the knee (passive flexion ROM < 
90); hip (inability to achieve neutral 0° hip extension); or ankle (inability to achieve 0° of active 
dorsiflexion); 4) history of congestive heart failure, unstable cardiac arrhythmias, hypertrophic 

Lower extremity power and locomotor function after stroke      18 
 
cardiomyopathy, severe aortic stenosis, angina or dyspnea at rest or during ADL’s; 5) History of 
COPD or oxygen dependence; 6) Preexisting neurological disorders, dementia or previous stroke; 
7) History of major head trauma; 8) Legal blindness or severe visual impairment; 9) history of 
significant psychiatric illness 10) Life expectancy <1 yr., 11) Severe arthritis or other problems 
that limit passive ROM; 12) post-stroke depression (PHQ-9 ≥10), 13) History of DVT or pulmonary 
embolism within 6 months; 14) Uncontrolled diabetes with recent diabetic coma, or frequent 
insulin reactions; 15) Severe hypertension with systolic >200 mmHg and diastolic >110 mmHg at 
rest; 16) Previous or current enrollment in a trial to enhance motor recovery; 17) Presence of non-
MR compatible implants, pregnancy or severe claustrophobia.  
Subject recruitment: The combination of the Ralph H. Johnson VAMC and the MUSC Stroke 
Center provide a unique environment from which to recruit participants (Veteran and non-veteran) 
for this study.  These two centers consist of highly trained neuroscience nurses, stroke 
neurologists, diagnostic neuroradiologists, dedicated case managers and social workers, many 
of whom hold dual appointments (VA + MUSC). The MUSC program holds Joint Commission's 
Certificate of Distinction for Primary Stroke Centers which recognizes centers that make 
exceptional efforts to foster better outcomes for stroke care. The Stroke Center research team 
will assist with recruitment by reviewing previous patient rosters to identify potential participants. 
Potential participants will be given information while inpatient and again when they are seen for 
follow up in the outpatient clinic at the MUSC Stroke Center. The Stroke Center research team 
will establish communication with the potential participants and act as a liaison with the Principal 
Investigator to facilitate recruitment. The MUSC Stroke Center sees over 50 new stroke patients 
per month and routinely screens all patients for eligibility to our various research studies.  Thus, 
with such a large database of stroke patients, we should have no difficulty in recruiting the 
hemiparetic subjects required to address our aims. 
Subject screening and clinical assessments: After enrollment, participants will be thoroughly 
evaluated for functional and cognitive impairments as well as physical performance. Descriptive 
physical performance testing will include the lower extremity Fugl-Meyer, Stroke Impact Scale 
(SIS), Berg Balance Scale (BBS) and the NIH Stroke Scale. The lower extremity Fugl-Meyer is a 
34-point scale assessing lower extremity function through a progression of items examining more 
complex movements, speed, and coordination. The SIS is a stroke-specific outcome measure 
that assesses physical function and other dimensions of health-related quality of life: emotion, 
communication, memory and thinking, and social role function. The physical functioning domain 
includes strength, hand function, mobility, and activities of daily living. The NIH Stroke Scale 
measures stroke related impairments including level of consciousness, ability to respond to 
questions, ability to follow simple commands, deviation of gaze, hemianopsia, facial palsy, limb 
movements of paretic and non-paretic limbs, limb ataxia, sensory loss, neglect, dysarthria, and 
aphasia. We will also assess passive ROM of the paretic and non-paretic ankle and knee joints, 
spasticity (Modified Ashworth Scale) and sensation (Fugl-Meyer sensory) so as to be able to 
retrospectively determine the potential impact of these measures on response to training. In 
addition, the Folstein Mini-Mental Status will be used as a screen of cognitive function. 
Specifically, we will use the three-step command item as a primary screen for study eligibility. 
Finally, subjects will be screened for depression using the PHQ-9. We will exclude subjects with 
major depression (PHQ-9 score ≥ 10). All clinical assessments will be performed by a research 
physical therapist employed by the Department of Health Sciences & Research and is not 
involved in any other aspects of the proposed study.  
Exercise Tolerance Testing: For subjects enrolling in training, a bicycle ergometry protocol used 
successfully in the recently completed LEAPS trial (Duncan et al, 2007) will be used to assess 
exercise tolerance for inclusion in this study. The exercise protocol will commence with the subject 
seated on the bicycle ergometer with feet secured in toe clips. The subject will first sit quietly 

Lower extremity power and locomotor function after stroke      19 
 
without pedaling for two minutes. Exercise will begin with the subject pedaling at ~60 revolutions 
per minute (RPM) and 0 Watts (W) of workload. The workload will be increased by ~10 W every 
3 minutes. If the subject’s cadence drops below 50 RPM, additional reminders to pedal at 60 RPM 
will be given. Testing continues until maximal effort is achieved. Maximal effort is defined as the 
achievement of 90% maximal age-predicted heart rate (maximum heart rate = 220-age). The test 
will be terminated prior to achieving maximum heart rate for predefined symptomatic, clinical, and 
electrocardiographic criteria. Symptom-related reasons for termination include angina, dyspnea, 
and fatigue. Fatigue is defined as either voluntary exhaustion or inability to maintain a minimum 
cycling cadence of 40 RPM. Clinical criteria for termination include: 1) Hypertension: ≥ 220/120 
mmHg, or 2) Hypotension: a drop in diastolic blood pressure >20 mmHg, and O2 saturation <85%. 
Electrocardiogram criteria include: 1) ≥ 1 mm horizontal or down sloping ST segment depression, 
2) sustained paroxysmal ventricular tachycardia (>30 beats), and 3) sustained paroxysmal 
supraventricular tachycardia (>30 beats). A 5 minute cool down period will immediately follow test 
termination. If the test is terminated because of electrocardiographic findings, the subject will be 
managed medically as needed, referred for care, and disapproved for participation. Brachial artery 
blood pressure from the subject’s non-paretic upper extremity will be measured using an 
automated blood pressure monitor.  Resting blood pressure and heart rate will be obtained prior 
to initiation of exercise as well as after the subject has been sitting on the stationary bicycle for 1 
minute. During the graded exercise test, blood pressure readings will be obtained every 3 
minutes. Heart rate will be obtained from the 12-lead EKG. Maximal heart rate will be recorded 
as the highest heart rate achieved during the exercise tolerance test.    
Subject monitoring during testing and training: Blood pressure (BP) and heart rate (HR) will be 
monitored prior to, during, and at completion of each session. Subjects’ resting diastolic BP must 
be <100 mmHg, systolic < 200 mmHg, and heart rate <110 beats/min to begin the testing (Mahler 
et al, 1995, Rimmer et al, 2000). Criteria for termination include subject complaints of shortness 
of breath, light-headedness, confusion, severe headache, or dyspnea; onset of angina; excessive 
blood pressure (systolic BP > 200mm Hg, diastolic BP >110 mm Hg), or drop in systolic BP >10 
mm Hg and inappropriate bradycardia (drop in heart rate >15 bpm).  
Post-stroke Optimization of Walking using Explosive Resistance (POWER) training: 
Training to improve muscle power (vs. strength) is shown to be effective for improving functional 
mobility the aged (Costello et al, 2008) as well as in stroke survivors, (Lubetzky-Vilnai et al, 2010) 
though no single intervention has been proven most beneficial for optimizing outcomes. To date, 
there is a paucity of information regarding the physiological mechanisms underlying 
improvements in muscle power generation as they relate to improved walking and to understand 
the differences in those who respond versus those who do not. Accordingly, there is a need for 
systematic investigation to identify the relevant mechanisms to determine whether and how they 
adapt to rehabilitation interventions and further, how significantly therapeutically-induced 
neuromuscular adaptations translate to improved functional performance. The novel theoretical 
framework we have developed will allow us to address these issues with a thoroughness not 
previously feasible. Individuals with chronic post-stroke hemiparesis will undergo training to 
improve muscle power generation for 24 sessions (3 times/week) that includes both resistive and 
task-specific elements.  Session duration will be ~90 minutes/day (inclusive of rest intervals) 
although the total time spent in the laboratory will depend on the amount of rest needed for a 
given individual.  Training will include five distinct resistance activities aimed at improving muscle 
power-- each previously reported to contribute to improved walking (Figure 14). Sit to stand and 
leg press exercises are elements of programs shown to be effective in improving strength and 
walking performance in the post-stroke population (Tung et al, 2010; Duncan et al, 2007). 
Repeated step-up training using a single riser targets both eccentric and concentric training in 
both the sagittal and frontal planes.  As possible for individual subjects, we will utilize a step height 
higher than standard community steps (10”) to further challenge neuromuscular requirements of 

Lower extremity power and locomotor function after stroke      20 
 
the task. Calf raises (i.e. plantar flexion exercise) will be performed on a small step so as to allow 
for adequate range of motion. In addition, our pilot data demonstrate that jump training, focused 
on lower extremity muscle power generation, is part of a comprehensive program that improves 
gait speed in people with post-stroke gait deficits.  Sit to stand, step-up and calf raise activities 
will be performed within the novel overground body-weight support (BWS) environment enabled 
by the Zero-G (ZeroG, Bioness Inc., Valencia, CA), whether receiving support or not, to provide 
the maximum safety possible.  
During the initial training session, subjects will perform the individual component tasks beginning 
with least amount of BWS (or highest load) required for successful completion of the required 
number of repetitions in order to match the participant’s ability to the difficulty of the task 
(Guadagnoli and Lee, 2004).  BWS will be progressively reduced so as to determine the minimum 
level of support necessary for subjects to complete each task. The level of support required for 
successful completion of each task will be recorded over time to monitor and document 
progression of the program.  Participants will be progressed within each task by decreasing BWS 
by 5% of body mass (or adding 5% load for leg press) upon successfully meeting the goals for 
progression (see Figure 14).  An adjustable weighted vest will be utilized to increase mass by 5% 
during training for a given task once support is not required for successful task completion.  
Subjects will not be permitted to use assistive devices and physical assistance will not be provided 
during training.  A given task will be considered unsuccessful if physical assistance or a 
mechanical stop to prevent a fall is required.  
Sit to stand, leg press, step-up and calf raise activities will be performed under two conditions 
within each training session.  Condition 1 will include performing two sets of ten repetitions with 
the targeted amount of resistance for the given session and based on rate of progression 
throughout training.  Condition 2 will require the participant to perform as many repetitions as 
possible during a 20 second period utilizing either 80% of the resistance from Condition 1 or an 
increase in BWS of 20%. This condition is designed to encourage high velocity and hence high-
power output contractions. As much rest as needed between sets will be allowed beyond the  3 
minutes rest that will be required for all subjects. Given our focus on muscle power generation, 
all participants will be instructed to perform the concentric portion of each exercise at maximum 
velocity regardless of the prescribed condition, followed by a controlled eccentric contraction.  
This approach is adapted from programs specifically targeting power training in an aging 
population with mobility deficits and shown to result in significant increases in peak power 
generation when compared to slower velocity training, while achieving similar gains in strength 
Figure 14: Activities, task specifications and goals for progression during POWER training. * An 
alternative approach will be to perform these tasks using the ShuttlePro (i.e. in a supine position) if 
an individual cannot accomplish the task in an upright posture using the ZeroG. 

Lower extremity power and locomotor function after stroke      21 
 
(Fielding et al, 2002; Bean et al, 2004).   
For jump training, subjects will be familiarized with the equipment and, during the initial training 
session, will complete a total of 30 (3 sets of 10) bilateral ground contacts (jumps).  We will begin 
the first session at a resistance of ~20% of body mass. 
Based on individual subject ability, external resistance will 
be increased or decreased accordingly and resistance 
documented as a reference for subsequent sessions. The 
number of jumps will be increased to 45 in week two and to 
60 thereafter (the goal being to complete the prescribed # 
of jumps in 3 sets). Upon successful completion of at least 
60 ground contacts (e.g. complete clearance from foot plate; 
Figure 15), resistance will be increased in increments of 5 
lbs. or 5% body mass, whichever is greatest. As subjects 
feel comfortable, and no later than the beginning of week 4, unilateral jump training will be 
performed using each leg, the goal being to progress to a reciprocating jumping pattern (i.e. 
alternating legs each jump for a total of 60 jumps per leg). Throughout the training protocol, a 
minimum of two sessions at a given resistance will be required before load is increased and 
resistance will be held consistent between limbs throughout the training program. Session 
intensity will be systematically progressed and modified by changing either the applied resistance 
or the number of ground contacts. 
Progressive loaded overground fast walking: As part of each training session, subjects will 
perform 10 trials of fast overground walking (10 meter distance per trial). These trials are intended 
to emphasize the task-specific lower extremity power generation required to accomplish 
increased walking speeds. Subjects will be asked to complete all trials without an assistive device 
or ankle-foot orthosis at speeds ≥ 125% of self-selected overground velocity.  Although we will 
not allow the use of an AFO, subjects will be permitted to wear an ankle brace for medial-lateral 
support (AirCast®) that allows for plantarflexion and dorsiflexion voluntary movements. Subjects 
will walk over our instrumented walkway (GaitRite) so as to provide real time feedback of speed 
as well as spatio-temporal parameters of walking for each trial. These trials will also be performed 
in the ZeroG harness to protect the subject in the case of a loss of balance as well as to provide 
body-weight support as needed to facilitate walking at the required speeds. Subjects will begin at 
the level of BWS that allows them to successfully complete the 10 trials at an average of ≥125% 
of self-selected speed. After each training session the average speed will be calculated and 
compared to the self-selected speed. When the average speed exceeds 125% of self-selected 
speed, we will decrease BWS by 5% for the next training session. At the point when subjects are 
able to successfully exceed 125% of self-selected speed without body-weight support, a weighted 
vest will be worn and mass systematically added to allow progression. Note that in order to provide 
the optimal stimulus for increasing propulsion, we will provide an amount of BWS to offset to the 
added mass. This has been shown to engage the muscles most responsible for generating 
propulsion to a greater extent (McGowan et al., 2008) and should optimize the power training 
stimulus for the muscles generating propulsion.  
It is important to point out that progression for muscle power training and overground stepping 
will be accomplished via reduction in BWS (or added mass) as tolerated, allowing for increased 
“resistance” and graded exercise. The overground permissive environment allows safe training 
without assistive devices or and allows determination of the precise ability level of the individual 
for a task.  In creating a constant permissive environment, we are able to identify precisely how 
much support is required for independent completion of the task while simultaneously eliminating 
falls risk.  This environment allows the participant to engage in therapy at a consistently more 
challenging level than is allowed in conventional rehabilitation.  This approach is based on a 
Figure 15: Exercise apparatus used for jump training task 

Lower extremity power and locomotor function after stroke      22 
 
philosophy known as the “challenge point framework”, which theorizes that one’s ability level is 
defined by the level of difficulty at which one has an equal (50%) chance of success or failure 
(Guadagnoli and Lee, 2004), a level of difficulty that is rarely matched in clinical rehabilitation due 
to increased potential for falls.   
Overground self-selected walking practice: In addition to progressive fast walking to emphasize 
task-specific power generation, subjects will also perform 10 min. of overground walking at a self-
selected velocity in each session.  The goal for this activity is continuous walking (as possible) 
and is designed to allow for regular, safe practice of newly acquired capacity. Rest as needed will 
be allowed. This training element is consistent with the amount of overground walking performed 
as part of our recently completed study of task-specific locomotor training (RR&D B3983-R; Kautz 
PI). Subjects will initially perform overground walking in the safety harness without bodyweight 
support but will progress to independent overground walking.  We believe that progressive safe 
practice incorporating the increased power generating capacity (neural mechanisms could result 
in changes quite quickly) without initially needing to worry about the balance challenge is most 
appropriate. The distance walked during each session will be recorded to monitor improvements 
over the 8 week training period. 
Dynamometric Assessment: Isometric and isotonic assessments will be performed at the hip 
(flexion only), knee (flexion/extension) and ankle (plantar flexion/dorsi-flexion) prior to, after 4 
weeks and following 8 weeks of POWER training. Assessments will be performed using a Biodex 
isokinetic dynamometer (Biodex Corp., Shirley, NY). Prior to testing, each subject will go through 
a period of familiarization and warm-up consisting of 5 minutes of cycling and three sub-maximal 
contractions for each joint action. During isometric testing, maximum voluntary isometric 
contraction (MVIC) will be defined as the highest isometric torque achieved during 3 maximal 
contractions (~3 sec contractions separated by a minimum of 60 seconds rest).  In the event that 
the MVIC values during the three trials differ by more than 5%, additional contractions will be 
performed. In addition to MVIC, values for the average rate of torque development (ARTD) will be 
calculated in the corresponding time interval between 20% and 80% of MVIC. (Gregory et al., 
2007) This time interval was chosen to minimize potential errors in the determination of the precise 
onset and nadir of torque development while still representing a majority of the time necessary 
for achieving maximal torque production. ARTD is defined as the average increase in torque per 
unit time, and calculated by numerical differentiation as:   
ARTD = 1
N
δfi
δt
i=1
N
∑
 
Where, N  is the total number of time slots for numerical differentiation, δfiis the change in torque 
in the time slot i and δt is the unit time duration for a slot. 
During isotonic testing, peak power will be assessed using 40% of MVIC. Differences in lower 
extremity maximal velocity are shown to occur at relatively low external forces (e.g. 40% 1 RM) 
and are most closely associated with gait velocity in older individuals. (Bean et al., 2002) To 
optimize reliability of the testing, each test will be repeated 3 times. If the coefficient of variation 
among the 3 highest powers is > 10%, additional contractions will be performed. Power-angle 
curves will be plotted and the peak powers recorded.  
During all dynamometric testing, subjects will be instructed to (1) develop torque as fast as 
possible and (2) produce a maximal contraction. Subjects will be given an auditory cue and 
receive continuous visual feedback. All contractions will be performed with subjects positioned in 
the dynamometer and the axis of the dynamometer aligned with the joint axis of rotation. Proximal 
stabilization will be achieved with straps at the chest, hips, and knee as appropriate. In order to 
increase sensitivity, the force transducer signal will be amplified and fed into a data acquisition 

Lower extremity power and locomotor function after stroke      23 
 
unit (Lab View Inc.) and corrected for the effects of gravity. 
Central Activation: Central activation will be determined in the plantar flexor and knee extensor 
muscles using the twitch interpolation method. Briefly, a single biphasic, supra-maximal electrical 
pulse will be delivered at rest and during maximal contractions. Activation deficits will be 
calculated using the ratio between the torques produced by the superimposition of a supra-
maximal twitch on the maximal contraction and by the same stimulus in the potentiated resting 
muscle, as previously reported (Gregory et al., 2007). Electrical stimuli will be generated using a 
Grass S8800 stimulator and delivered through surface electrodes placed over the proximal and 
distal portions of the muscles. The stimulator and the dynamometer will be interfaced with a 
personal computer through a commercially available hardware system (MP150). Data will be 
sampled at 400Hz using commercially available software (AcqKnowledge 3.7.1).  
Experimental protocol for MRI data collection: 3D-Magnetic Resonance Imaging will be 
implemented to quantify the maximal cross-sectional area of the flexor and extensor muscles 
about the hip, knee and ankle. Briefly, once subjects reach the MR facility, they will remain in a 
supine position for 30 minutes prior to imaging. All imaging will be performed in a 3.0 Tesla magnet 
(Siemens) using either a body coil or a standard quadriture extremity coil (ankle). 3D data will be 
acquired using a fast gradient-echo sequence with TR=100 ms, TE=10ms, flip angle=30°, an 
encoding matrix of 256x256, field of view of 16-24cm and 7mm slice thickness. Muscle and non-
muscle tissue will be differentiated and CSA measured via a publicly available software (Osirix®). 
Experimental protocol for MRS data collection: Figure 16 shows the five peaks, corresponding 
to inorganic phosphate (Pi), phosphocreatine (PCr), and the three phosphates of ATP, that can 
be quantitated in a 31P spectrum.  By integrating the individual peaks, the amount of each 
metabolite can be estimated. Further, the position of the Pi peak is pH dependent so monitoring 
its position allows us to estimate intracuscular pH. The concentration of these bio-energetically 
important compounds, as well as the intracellular pH, can thus be monitored continuously, at rest 
as well as during exercise and recovery. Specifically, data collected during recovery are used to 
determine the muscle’s in-vivo oxidative capacity (Rossi et al, 1996; Kemp et al, 1994; Meyer, 
1988). This capacity is commonly inferred from the rate of PCr resynthesis following exercise (Blei 
et al 1993; Kemp et al, 1994; McCully et al, 1992). Based on these observations, a decreased 
muscle oxidative capacity has been demonstrated in various patient groups, including those with 
mitochondrial myopathies (Argov & Arnold, 2000), peripheral vascular disease (McCully et al, 
1992), multiple sclerosis (Kent-Braun, et al, 1994), and congestive heart failure (Rossi et al, 1996).  
31P-MRS data will be collected to determine the resting concentrations of inorganic phosphate [Pi] 
as well as the in-vivo oxidative capacity of the knee extensor and plantar flexor muscle groups. 
Oxidative capacity will be determined based on the rate of PCr resynthesis following repeated 
plantar flexor contractions at ~30% maximal voluntary contraction (MVC). An exercise device will 
be utilized for 31P-MRS data collection that consists of an MR-compatible foot pedal attached to 
a force transducer and adjustable load.  31P-MRS data will be collected using a standard pulse-
acquire sequence on a 3.0 Siemens Trio scanner with a 4.5 cm circular transmit-receive surface 
coil. The voxel for localized spectra will be prescribed based on images obtained using a 3D 
gradient echo imaging sequence (field of view = 14x14 cm, 1 NEX, a minimum pulse repetition 
time (~20 ms), and an echo time of 2 ms). ). In order to acquire 
accurate resting 31P MRS spectra we will initially acquire 
spectra with 256 averages (TR = 5 s, spectral width of 6000 
Hz, 2048 data points). 31P-MRS kinetic data will be acquired 
with the same parameters but with only 2 averages at rest, 
during exercise, and recovery giving us a time resolution of 10 
seconds.   
Figure 16: Illustration of phosphorous containing 
compound peaks during 31P-MRS of the calf muscles. 

Lower extremity power and locomotor function after stroke      24 
 
Data Processing: Resting spectra will be manually phased and the areas of the βATP, Pi, and 
PCr peaks integrated. PCr levels during exercise will be measured using complex principal 
component analysis of the entire time series, as previously described (Stoyanova, Brown et al., 
2001). PCr recovery data will be fitted to a single exponential curve, and the psuedo-first-order 
rate constant (kPCr) determined as follows: 
PCr (t) = PCr0 + ∆PCr (1-e –kt) 
where PCr is the concentration of PCr at a given time t during recovery; PCr0 is the PCr 
concentration at end of exercise and ∆PCr is the change in PCr concentration after recovery. The 
maximal rate of PCr resynthesis (Vmax-lin) (a measure of mitochondrial ATP resynthesis) will be 
calculated based on kPCr and PCr rest (Vmax-lin = kPCr [PCr] rest). 
Experimental protocol for walking data collection: At the beginning of the session, subjects 
will walk on a 14 ft. long gait mat (GaitRite) to measure self-selected and fastest comfortable 
walking speed and other spatiotemporal parameters. Treadmill speed will then be set to the 
subject’s self-selected speed and fastest comfortable speed. Subjects will be permitted a practice 
trial, and then be asked to complete three trials at each speed during which kinematic, kinetic and 
EMG data will be captured. To optimize capture of steady state data, each subject will walk for 
~10 sec prior to the 20 sec of data collection; therefore, each trial duration is 30 sec. This will 
allow capture of ~10 consecutive steady state gait cycles per trial (depending on cadence). A 
modified Helen Hayes reflective marker set will be recorded using a 12-camera motion analysis 
system (PhaseSpace) to capture bilateral 3D kinematics. A 16-channel EMG system (Motion Labs 
Systems) will be used to record bilaterally from: medial gastrocnemius, soleus, tibialis anterior, 
rectus femoris, vastus medialis, biceps femoris, semimembranosus, and gluteus medius. Bilateral 
ground reaction forces, moments and center of pressure will be captured during split-belt treadmill 
walking via two force plates embedded in the instrumented treadmill (Bertec). For all trials, 
subjects will wear their own shoes and be asked to walk without an assistive device or ankle-foot 
orthosis (see Potential Limitations). A safety harness mounted to the ceiling will protect the 
subject but will only support their body weight in the case of a loss of balance. A physical therapist 
will be present for all testing sessions as needed. Data processing: EMG and ground reaction 
force data will be collected at 1000 Hz. Raw EMG will be high-pass filtered using a fourth-order, 
zero-lag digital Butterworth filter (20 Hz cutoff) to eliminate movement artifact. We will then 
subtract the mean value, rectify and low-pass filter the data with a fourth-order, zero-lag digital 
Butterworth filter to produce linear envelopes. Kinetic and kinematic data will also be low-pass 
filtered with fourth-order, zero-lag digital Butterworth filter (20 and 9 Hz cutoff frequencies). Inter-
segmental joint moments (normalized by body mass) and powers (product of moments and 
angular velocity) will be calculated using standard 3D inverse dynamics techniques and time 
normalized to 100% of the paretic leg gait cycle. The typical propulsive regions of the ipsilateral 
gait cycle will be divided into late single-leg stance (i.e., second 50% of single-leg stance) and 
pre-swing (i.e., double support region preceding toe-off) regions. Sagittal plane hip (flexor 
positive), knee (extensor positive) and ankle (plantarflexor positive) joint moment impulses and 
the AP GRF impulse (AP impulse) will be calculated for each region. A muscular utilization ratio 
(Milot et al, 2007) will also be calculated by dividing the peak power during walking by the peak 
power during dynamometric testing in PF and KE.     
Measure of neural activation coordination: Neural activation coordination will be assessed 
from the eight channels of EMG collected in the paretic leg similar to our published work (Clark, 
2010). Muscle activation signals (EMGs) will be demeaned, rectified, and smoothed with a zero 
lag fourth-order low-pass (4 Hz) Butterworth filter. To facilitate comparisons between subjects and 
among different walking speeds, the EMG from each muscle will be normalized to its peak value 
from self-selected walking and resampled at each 1% of the gait cycle. For each subject, leg, and 
walking speed, the EMGs will be combined into an 8 x t matrix (EMGo), where 8 indicates the 

Lower extremity power and locomotor function after stroke      25 
 
number of muscles and t is the time base (t = no. of strides x 101). For each subject, an NNMF 
algorithm (Lee & Seung, 1999; Ting and MacPherson, 2005; Clark et al., 2010) will be applied to 
the 8 x t matrix corresponding to all gait cycles from SS trials. A priori, the number of independent 
co-activation patterns (ICPs), n, is specified, and the non-negative matrix factorization (NNMF) 
algorithm finds the properties of the ICPs by populating two matrices: an 8 x n matrix, which 
specifies the relative weighting of a muscle in each ICP, with each muscle weight invariant across 
all gait cycles, and an n x t matrix, which specifies the activation timing of each ICP over each of 
the gait cycles. When these two matrices are multiplied, an 8 x t matrix is produced that attempts 
to reconstruct the EMGs over all of the consecutive gait cycles. Of note, NNMF allows muscles 
to belong to more than one ICP and that a muscle’s reconstructed EMG is the summed 
contributions from all the ICPs. The 8 x t matrix of the reconstructed EMGs (EMGr) is compared 
with the original EMG matrix (EMGo) and the agreement quantified by calculating the sum of the 
squared errors: (EMGo – EMGr)2. Within this framework, the NNMF algorithm performs an iterative 
optimization until it converged on the muscle weights and the activation timings of the modules 
that minimize the error.  
We make no a priori assumptions regarding the number of ICPs that will be required to adequately 
reconstruct the EMG signals. Therefore separate NNMF analyses are performed with the output 
constrained to one, two, three, or four ICPs. To determine the minimum number of ICPs needed 
to adequately reconstruct EMGo in each leg of each subject, we calculate the variability accounted 
for (VAF) as the ratio of the sum of the squared error values to the sum of the squared EMGo 
values [VAF = 1 - (EMGo–EMGr)2/EMGo 2]. VAF is calculated for each muscle across all gait 
cycles. To ensure that EMG was adequately reconstructed within each region of the gait cycle, 
VAF is also calculated as the cumulative of all muscles within each of six regions for all gait cycles. 
The regions are defined as 1) first double support, 2) first half of ipsilateral single leg stance, 3) 
second half of ipsilateral single leg stance, 4) second double support, 5) first half of ipsilateral 
swing, and 6) second half of ipsilateral swing. The analysis for each subject begins by assuming 
that only one ICP is needed for EMG reconstruction. If VAF was ≥ 90% for each of the eight 
muscles and six regions, it is determined that additional ICPs are not needed. Otherwise, the 
number of ICPs assumed is increased until all muscles and regions achieve 90% VAF or until 
adding an additional ICP does not increase VAF by > 5% for the muscle(s) and/or region(s) with 
the lowest VAF. This approach is conservative and ensures a strong agreement between the 
original and reconstructed EMG signals. 
Independence of the plantarflexor (PF) and knee extensor (KE) muscle groups will be 
categorized as a true or false value based on the number and composition of ICPs. In healthy 
subjects soleus and gastrocnemius are the primary muscles in an ICP that is active during the 
second half of stance and the KE are active with gluteus medius as the primary components of 
an ICP that is active in early stance (Clark et al., 2010). Hemiparetic subjects with only two ICPs 
merge the PF and KE ICPs with a third ICP (that primarily includes the hamstrings and is active 
in late swing and early stance) into a mass extensor ICP that is active the entire stance phase 
(Clark et al., 2010). Thus, subjects with two ICPs do not have independence for either muscle 
group. Subjects with three or four ICPs will be classified as independent in PF if they have one 
ICP that includes primarily soleus and gastrocnemius and in KE if they have one ICP that includes 
primarily vastus medialis, rectus femoris and gluteus medius. Timing of neural activation will be 
assessed by quantifying the percent of time that a muscle is active during specified regions of the 
gait cycle based on normal activation patterns. Specifically, we will calculate these quantities 
during the region of primary activity when the muscle should be “on” and during a stance phase 
region when the muscle should be “off” (e.g., a region when the muscle group’s primary ICF is 
not active during healthy gait but active when the subject has only two ICFs). For PF the “on” 
region is from mid-single leg stance to toe-off and the “off” region is during initial double support. 
For KE the “on” region is the initial double support phase and the “off” region is second double 

Lower extremity power and locomotor function after stroke      26 
 
support phase. Overall coordination of walking will be quantified by the number of ICFs found 
for the subject. 
Clinical Assessments: The assessments are standard to most post-stroke intervention trials. 
Including these assessments strengthens our design by allowing us to make conclusions 
regarding the effects of our intervention that extend beyond the behavioral measures of walking. 
We feel that the proposed benefits of our training will be most significant if they are shown to 
impact behaviors other than that which is targeted as the primary outcome and relate to other 
domains of function suggested to put individuals post-stroke at risk for disability. All clinical 
assessments will be performed by a staff physical therapist within the Center for Rehabilitation 
Research in Neurological Conditions who will be blinded to responses to training. 
 Dynamic Gait Index (DGI): The DGI evaluates the ability to adapt to changes in task demands. 
The DGI rates performance from 0 (poor) to 3 (excellent) on eight different gait tasks, including 
even surfaces, changing speeds, head turns in a vertical or horizontal direction, stepping over 
or around obstacles, and gait with pivot turns, and steps (Shumway-Cook et al, 2001). The DGI 
examines complex walking tasks (e.g. accelerating, turning, head turns) and provides valuable 
information regarding dynamic balance (as opposed to static balance assessed using the BBS) 
and often reveals deficits that otherwise would not be identified.   
 Step Activity Monitor (SAM): The SAM is worn on the ankle to quantify daily step activity. The 
SAM is a microprocessor-driven accelerometer that permits the researcher to count strides and 
observe activity during predetermined time spans. The SAM is 98%-99% accurate and has a 
test-retest reliability post-stroke of 0.98. (Mudge et al., 2007)  The SAM will be worn for two 
consecutive days at a 6-second epoch, per the LEAPS protocol (Duncan et al, 2007).  
Information about the effects of POWER training on the amount of community stepping are 
critical as we attempt to generalize any improvements beyond the laboratory. 
 6-Minute Walk Test (6MWT): Timed walking tests are primarily a measure of functional capacity 
(Solway et al, 2001). The 6MWT tests populations who present with little functional walking 
capacity and has been validated against the Rivermead Mobility Index (r=0.75) and 10-meter 
walk time (r=-0.61).(Rossier et al, 2001) The 6MWT has a high intra- and interrater reliability 
(ICCs = 0.82-0.95) (Wade, 1992).  
 Stroke Impact Scale (SIS): The SIS assesses physical function as well as other dimensions of 
health-related quality of life: emotion, communication, memory & thinking, and social role 
function. The SIS was created to assess changes in impairments, disabilities and handicaps 
following stroke, but has been validated for repeated administration over time, in clinical and 
research settings (Duncan et al., 2003 a,b,c). 
Projected Timetable: 
• 
Project Development:  The first quarter (Months 1-3) of Year 1 will be devoted to finalizing 
imaging sequences for MRI and 31P-MRS studies and establishing the data acquisition 
pipeline for dynamometric and biomechanical data collections. 
• 
Subject Recruitment: Recruitment of participants will begin early in the first quarter of the 
project period and will continue through the third quarter of year three. 
• 
Longitudinal Evaluations: Baseline evaluations prior to POWER training will take place 
beginning in Quarter 2 of Year 1 and continuing through the end of Year 3.  We will evaluate 
muscular function and perform MR imaging and spectroscopy studies to determine muscle 
power, central activation, muscle cross-sectional area, [Pi] and in-vivo oxidative capacity of 
the plantar flexor and knee extensor muscle groups.  
• 
Therapeutic Intervention:  Beginning in Quarter 2 of Year 1 and continuing through Quarter 2 
of Year 4, hemiparetic subjects will participate in 8-weeks of POWER training. 

Lower extremity power and locomotor function after stroke      27 
 
• 
Follow-up Evaluations:  Post-training evaluations will be conducted 8 weeks following 
POWER training.  Assessments performed at pre- and post-training will be repeated during 
follow-up evaluation. 
• 
Data Analyses: Data analysis will begin beginning in Year 3 and throughout the remainder of 
the project.  
• 
Dissemination:  Data dissemination will take place as appropriate, but not earlier than in Year 
3, via meeting abstracts as well as full publications. 
Sample size determination and Statistical Approach: A total of 28 subjects will be recruited 
for this study.  With baseline data from n=28 subjects, we will have at least 80% power to detect 
measures of association (i.e. partial correlations) as small as 0.5 between neural/muscular 
adaptations and peak power generation.  Our preliminary data suggest that the intraclass 
correlation between measures of power on paretic and non-paretic legs is extremely high (i.e. 
Spearman rho = 0.81, intraclass correlation coefficient [ICC - from mixed model] ~100%).  This 
power estimate for Aim 1 is based on 1 observation per subject; although our mixed model 
approach for analyses for Aim 1 will include 2 observations per subject (i.e. paretic and non-
paretic leg), the detectable correlation may not be substantially lower due to the strong intraclass 
correlation.  For Aims 2 and 3, analyses rely on longitudinal measures, and we assume (based 
on experience with our patient population) that no more than 15% will fail to complete all 
assessments.  With 28 subjects enrolled and a 15% attrition rate over time (resulting in complete 
data on 24 subjects), we would have at least 80% power to detect changes in measures from 
baseline to the end of the study equivalent to 0.6 standard deviation units (i.e. effect sizes).  This 
power estimate is based on a paired t-test framework (i.e. pre-post comparisons), and thus power 
is likely underestimated, since our models will also include data from mid-intervention and follow-
up time periods.  For example, assuming an ICC of 90% associated with within-subject responses 
over 4 time periods, the effective sample size (see Campbell et al., 2001) would be slightly higher 
(~n=26), as would be our power (~83%) to detect an effect size of 0.6.  Treatment effect sizes of 
0.6 are consistent with our preliminary data, in which effect sizes of 0.7 (95% CI 0.5 to 0.9), 1.5 
(95% CI 1.1 to 1.9, and 0.5 (95% CI 0.1 to 1.0) were observed for improvement in gait speed, 
paretic leg power, and non-paretic power, respectively.  With complete data on 24 subjects, we 
will also be able to detect whether as little as 40% of the variability in changes in gait speed can 
be explained by changes in the neural / muscular adaptation measures, assuming an ICC of 90% 
associated with within-subject responses over 4 time periods.  All power estimates assume 2-
sided hypothesis tests and an alpha level of 0.05 and were conducted by a biostatistician using 
PASS 2008 (NCSS, Kaysville, Utah). 
E.  PROTECTION OF HUMAN SUBJECTS 
1. Risks to the subjects  
a. Human Subjects Involvement and Characteristics: We will recruit twenty-eight subjects with 
persistent motoric disability following a single stroke or two strokes on the same side of the brain, 
the most recent no less than six months prior. Subjects may be between 50 and 70 years of age, 
of either sex, and of diverse ethnic background. Subjects who have experienced more than one 
stroke will be accepted only if all strokes are on the same side of the brain, there is no history of 
a clinical ischemic or hemorrhagic event affecting the other hemisphere, and there is no evidence 
of more than a lacune or minor ischemic demyelination affecting the other hemisphere. Subjects 
will be recruited to participate in 8-weeks of a high-velocity resistance training paradigm designed 
to target lower extremity power generation. We will perform comprehensive dynamometric and 
magnetic resonance assessments of the paretic and non-paretic hip, knee and ankle musculature. 
In addition, we will also perform analysis of over-ground walking on an instrumented treadmill. 
During walking we will collect: (i) kinetics (3-dimensional ground reaction forces and moments), 

Lower extremity power and locomotor function after stroke      28 
 
(ii) kinematics (3-D) and iii) EMG from each leg as well as self-selected and fastest comfortable 
walking velocities. We will also perform a battery of clinical assessments to evaluate degree of 
function and disability. In addition to our post-stroke participants, we will also recruit twenty-eight 
neurologically healthy controls matched on the basis of age, gender, height and weight.  Control 
subjects will participate in dynamometric and magnetic resonance evaluations but will not 
complete the training. 
Subjects (male and female), ages 50-70, will be screened and recruited for the study six months to two 
years post-stroke, allowing for natural recovery during the first 6 months post-stroke. The pool of candidates 
for the study will be recruited from rehabilitation programs at the Ralph H. Johnson VAMC; the Medical 
University of South Carolina; and Charleston area communities. Eligible participants will be screened for 
participation and if appropriate will be accepted into the study for training.  
Inclusion criteria will be: 1) age 50-70, 2) stroke within the past 6 to 24 months, 3) residual 
paresis in the lower extremity (Fugl-Meyer LE motor score <34), 4) ability to walk without 
assistance and without an AFO on the treadmill ≥ 30 seconds at speeds ranging from 0.3 - 0.8 
m/s, and 5) provision of informed consent. In addition, all subjects who meet criteria for the training 
portion must complete an exercise tolerance test and be cleared for participation by the study 
cardiologist. Exclusion criteria will be: 1) Unable to ambulate at least 150 feet prior to stroke, or 
experienced intermittent claudication while walking; 2) history of congestive heart failure, unstable 
cardiac arrhythmias, hypertrophic cardiomyopathy, severe aortic stenosis, angina or dyspnea at 
rest or during ADL’s; 3) History of COPD or oxygen dependence; 4) Preexisting neurological 
disorders, dementia or previous stroke; 5) History of major head trauma; 6) Legal blindness or 
severe visual impairment; 7) history of significant psychiatric illness 8) Life expectancy <1 yr., 9) 
Severe arthritis or other problems that limit passive ROM; 10) post-stroke depression (PHQ-9 
≥10), 11) History of DVT or pulmonary embolism within 6 months; 12) Uncontrolled diabetes with 
recent weight loss, diabetic coma, or frequent insulin reactions; 13) Severe hypertension with 
systolic >200 mmHg and diastolic >110 mmHg at rest; 14) Previous or current enrollment in a 
clinical trial to enhance motor recovery; 15) Presence of non-MR compatible implants, pregnancy 
or severe claustrophobia.     
b. Sources of Materials: All data will be acquired for purposes of research only and will be kept 
confidential. Data will be coded and not traceable to individuals in any publication. Files will be 
stored in locked offices or password-protected servers dedicated to Dr. Gregory and key study 
personnel only. 
c. Potential Risks: The risks of the exercise tolerance tests are minimal but could include fainting, 
falling, irregular heartbeat, and very rarely heart attack, stroke, or death (less than 1 in 2500 
cases). Professional staff (exercise physiologist, physical therapist, and cardiologists) will be 
present and available throughout and emergency treatment will be available if it becomes 
necessary.  
There are no significant risks to the subjects in the proposed training methods. The risks to 
individuals participating in this study are no greater than the risks when providing conventional 
physical rehabilitation services to an individual after stroke. The same precautions and safety 
guidelines will be taken that are provided in patient care in rehabilitation settings. The 
rehabilitation program and the muscle and functional performance testing should not present a 
risk for the patient but could result in muscle soreness and/or joint stiffness but these symptoms 
should not persist more than a few days. There is a minimal risk for muscle strains during the 
testing and training. Under the conditions proposed for this project, MRI is not known to harm 
living systems. The electrical stimulation may be moderately uncomfortable at times, but is 
expected and typical for use of electrical stimulation and is not harmful. The discomfort is 
temporary and lasts only a few seconds. The locomotor assessments used in the proposed study 
are routine, clinical assessments of gait used in physical therapy clinics and rehabilitation 

Lower extremity power and locomotor function after stroke      29 
 
facilities. The GaitRite system has been used to assess walking performance with no adverse 
reactions or report of discomfort. The experimental protocol to be used in this portion of the 
proposal involves minimal risk, and is considered standard clinical practice. During all treadmill 
walking trials, a safety harness will be worn and a physical therapist will be present to provide 
assistance in the event of loss of balance. The harness will be designed to eliminate the 
consequences of falling as the device “catches” the subject should they trip or stumble. The 
presence of this device affords comfort and diminishes the “fear of falling” in subjects. 
2. Adequacy of Protection Against Risks:  
a. Recruitment and Informed Consent: A total of fifty-six subjects (male and female; n=28 post-
stroke and n=28 controls), ages 50-70, will be screened and recruited for the proposed study. The 
pool of post-stroke candidates for the study will be recruited from the Ralph H. Johnson VAMC; 
the Medical University of South Carolina; and the Charleston, SC area communities. Before any 
tests are conducted, the protocol and tests to be used in this study and the potential risks and 
benefits of participation will be explained to each potential subject. All participants will review and 
sign an informed consent form approved by the local Institutional Review Board prior to initiating 
any portion of the study.   
b. Protection Against Risk: A licensed physical therapist will be present during all treatment 
sessions.  In addition, during all treadmill walking trials, a safety harness will be worn to provide 
assistance in the event of loss of balance. The research staff will closely monitor the subject to 
ensure their comfort. Any adverse events will be recorded and monitored as required by our 
Institutional Review Board. In the event of an adverse medical event, standard facility emergency 
procedures will be followed and proper personnel notified. The PI on this proposal and is a 
licensed physical therapist with several years of experience in the development and 
implementation of exercise interventions. Any adverse events will be recorded and monitored as 
required by the IRB. On-site medical services will be available in the event of adverse events to 
the subjects. Subjects will be able to terminate the training or testing sessions at their request at 
any time without prejudice. Minimization of risk will be accomplished by monitoring vital signs 
within prescribed criteria for termination of the training session. We will follow the American 
College of Sports Medicine criteria for terminating an inpatient exercise session which includes: 
subject complaints of light-headedness, confusion, or dyspnea; onset of angina; excessive blood 
pressure changes (systolic BP greater than 220 mmHg, diastolic BP greater than 110 mmHg); 
and inappropriate bradycardia (drop in heart rate >10 beats per minute). 
Confidentiality: All records regarding participation in this study will be kept in locked file cabinets 
in 
the 
appropriate 
laboratories 
and/or 
offices, 
and 
stored 
on 
password-protected 
computers/servers in the offices and laboratories of the PI’s research team. There will be no direct 
link to participant identifying information (other than subject code) without access to a password-
protected computer containing the identifying information linking information to a given subject. 
Access to linked identifiers is limited to research personnel intimately involved with the human 
subjects. All data and records acquired from subjects is for research purposes only and will be 
kept confidential and maintained in a secure database identifiable only by subject code. The 
results of the study may be published for scientific purposes; however, subjects’ identities will not 
be revealed and data will not be traceable to any individuals in any resultant publications. The 
information gathered during this study will be kept confidential to the extent permitted by law. 
3. Potential Benefits of the proposed research to the subjects and others: Subjects with 
muscle dysfunction who participate in this study may see improvements in their own functional 
ability and strength, but any benefit cannot be guaranteed.  Others may benefit from advancement 
of scientific knowledge.  Given the minimal risks involved and the potential for improved functional 
capacity, the potential benefits of participation make the potential risks reasonable.   

Lower extremity power and locomotor function after stroke      30 
 
4. Importance of the knowledge to be gained: A better and more specific scientific 
understanding of muscular changes resulting post-stroke and following rehabilitation intervention 
may ultimately lead to a better understanding of muscle plasticity and the extent to which training 
restores muscle function and locomotor ability. Further, the data obtained during the process 
evaluation regarding the facilitators and barriers to implementation will be critical to bridge the 
gap between efficacy and effectiveness and will provide rationale for future studies.  Given the 
minimal risks involved and the potential to add to the limited base of scientific knowledge 
describing this population, the potential risks are reasonable.   
5. Statement of Inclusion of Women and Minorities in Research: This research will include 
women and minorities to the extent reflected by composition of the population in Charleston, SC 
and its surrounding areas. There are no exclusion or inclusion criteria which would exclude or 
preclude women or minorities from participating in this study. 
 
F. 
REFERENCES/LITERATURE CITATIONS 
1) Grillner S, Control of locomotion in bipeds, tetrapods and fish, In: Handbook of Physiology, J Brookhart, 
V Mountcastle and V Brooks, Ed. American Physiological Society: Bethesda, MD: 1179-1236, 1981.    
2) Rossignol S, Neural control of stereotypic limb movements. In: Handbook of Physiology, Section 12: 
Exercise: regulation and Integration of multiple systems, L Rowell and J Shepherd, Ed. American 
Physiological Society: 173-216, 1996.    
3) Brouwer B and Ashby P. Corticospinal projections to lower limb motoneurons in man. Exp Brain Res, 
89: 649-654, 1992.    
4) Grillner S. Possible analogies in the control of innate motor acts and the production of sound in speech, 
In: Speech Motor Control, S Grillner, Ed. Pergamon Press: New York: 217-229, 1982. 
5) Yates, J.S., et al., Bicycle ergometry in subacute-stroke survivors: Feasibility, safety, and exercise 
performance. Journal of Aging and Physical Activity, 12(1): p. 64-74, 2004.   
6) Bushnell, C.D., D.C. Johnston, and L.B. Goldstein, Retrospective assessment of initial stroke severity: 
comparison of the NIH Stroke Scale and the Canadian Neurological Scale. Stroke, 32(3): p. 656-60, 
2001.   
7) Studenski, S.A., et al., Predicting stroke recovery: three- and six-month rates of patient- centered 
functional outcomes based on the Orpington prognostic scale. J Am Geriatr Soc, 49(3): p. 308-12, 
2001.   
8) Folstein, M.F., S.E. Folstein, and P.R. McHugh, "Mini-mental state". A practical method for grading the 
cognitive state of patients for the clinician. J Psychiatr Res, 12(3): p. 189-98, 1975.   
9) Folstein, M.F., L.N. Robins, and J.E. Helzer. The Mini-Mental State Examination. Arch Gen Psychiatry, 
40(7): p. 812, 1983.   
10) Duncan P, et al. Randomized clinical trial of therapeutic exercise in subacute stroke. Stroke. 34:2173-
80, 2003.   
11) Mahler DA, Froelicher VF and Miller NH. The American College of Sports Medicine’s Guideline for 
Exercise Testing and Prescription, 5th Edition, Philadelphia, PA: Williams & Wilkins, 1995.   
12) Dobkin BH, et al., Methods for a randomized trial of weight-spupported treadmill training versus 
conventional training for walking during inpatient rehabilitation after incomplete traumatic spinal cord 
injury.  Neurorehabil Neural Repair, 17(3): P. 153-67, 2003. 
13) AHCPR. Clinical practice guideline: post-stroke rehabilitation. Rockville, MD: AHCPR; 1995. 
14) CM Gregory, M Bowden, A Jayaraman, P Shah, A Behrman, S Kautz & K Vandenborne. Resistance 
training and locomotor recovery after incomplete SCI: A Case Series. Spinal Cord 45(7): 522-30, 2007.    
15) Rossier P, Wade DT. Validity and reliability comparison of 4 mobility measures in patients presenting 
with neurologic impairment. Arch Phys Med Rehabil; 82(1):9-13, 2001.   
16) Bosco C and PV Komi. Influence of aging on the mechanical behavior of leg extensor muscles, Eur J 
Appl Physiol Occup Physiol, 45:209–219, 1980.    
17) A Jayaraman, P Shah, CM Gregory, M Bowden, J Stevens, AL Behrman & K Vandenborne. 
Locomotor training and muscle function after incomplete spinal cord injury: case series. Journal of 
Spinal Cord Medicine 31(2): 185-93, 2008. 
18) Moreau NG, Teefey SA, Damiano DL In vivo muscle architecture and size of the rectus femoris and 

Lower extremity power and locomotor function after stroke      31 
 
vastus lateralis in children and adolescents with cerebral palsy. Dev Med Child Neurol 2009; 51: 800-
806. 
19) Elliott MA, Walter GA, Gulish H, Sadi AS, Lawson DD, Jaffe W, Insko EK, Leigh JS and Vandenborne 
K. Volumetric measurement of human calf muscle from magnetic resonance imaging. MAGMA. 5:93-
8, 1997.   
20) Vandenborne K, Elliott MA, Walter GA, Abdus S, Okereke E, Shaffer M, Tahernia D and Esterhai JL. 
Longitudinal study of skeletal muscle adaptations during immobilization and rehabilitation. Muscle 
Nerve. 21:1006-12, 1998.   
21) Cumming RG, Salkeld G, Thomas M, Szonyi G. Prospective study of the impact of fear of falling on 
activities of daily living, SF-36 scores, and nursing home admission. J Gerontol A Biol Sci Med Sci; 
55(5):M299-305, 2000. 
22) Tinetti ME, Richman D, Powell L. Falls efficacy as a measure of fear of falling. J Gerontol; 45(6):P239-
43, 1990.   
23) Solway S, Brooks D, Lacasse Y, Thomas S. A qualitative systematic overview of the measurement 
properties of functional walk tests used in the cardiorespiratory domain. Chest; 119(1):256-70, 2001.   
24) Rossier P, Wade DT. Validity and reliability comparison of 4 mobility measures in patients presenting 
with neurologic impairment. Arch Phys Med Rehabil; 82(1):9-13, 2001.   
25) Wade D. Measurement in neurological rehabilitation. New York; Oxford Univ Press; 1992.   
26) Zajac FE, Neptune RR and Kautz SA. Biomechanics and muscle coordination of human walking. Part 
II: Lessons from dynamical simulations and clinical applications. Gait and Posture. 17:1-17, 2003.   
27) Bowden MG, Balasubramanian CK, Neptune RR, Kautz SA. Anterior-posterior ground reaction forces 
as a measure of paretic leg contribution in hemiparetic walking. Stroke. 2006, 37(3):872-6, 2006.  
28) Patterson SL, Forrester LW, Rodgers MM, Ryan AS, Ivey FM, Sorkin JD, Macko RF. Determinants of 
walking function after stroke: differences by deficit severity. Arch Phys Med Rehabil; 88(1):115-9, 2007.