Patient-Targeted Upper Extremity Rehabilitation After Stroke
Phase: NA
Conditions: Stroke
Sponsor: VA Office of Research and Development

 
 
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PI Name:  Michelle Woodbury, PhD, OTR/L 
 
Study Title:   Patient-Targeted Upper Extremity Rehabilitation After Stroke 
Version 4.0 
Date: 08/01/2016 
 
TABLE OF CONTENTS  
Specific Aims  
 
 
p.1 
Background and Significance  
p.2 
Preliminary Studies 
 
 
p.7 
Research Design and Methods 
p.12 
Protection of Human Subjects  
p.20 
References/Literature Citations 
p.25 
Consultants 
 
 
 
p.28 
Facilities Available 
 
 
p.29 
Investigator Brochure  
 
p.30 
Appendix 
 
 
 
p.30 
 
 
A. SPECIFIC AIMS___________________________________________________________________________ 
 
Exciting advances in rehabilitation research have increased knowledge about the potential for upper extremity 
(UE) motor recovery after stroke. Experimental models provide strong evidence that intensive task practice which 
is made progressively more and more challenging drives cortical reorganization. We restructured the Fugl-Meyer 
UE Assessment (FMA-UE) to reflect a progression of UE motor recovery typically seen in individuals with stroke. 
This novel restructuring (1) allows the identification of unique categories of UE motor impairment that can be the 
target for specific treatment, and (2) maps increasingly more difficult movement tasks for task-practice sessions. 
The restructured FMA-UE is the first comprehensive framework with which to link measurement of patient-specific 
UE motor ability to personalized treatment.  
 
The Specific Aims of this VA funded (VA Merit Award, #1I01RX000799, Woodbury PI) project are to: 
 
Aim #1: Compare the effects of targeted rehabilitation to non-targeted rehabilitation on UE motor function. 
 
Hypothesis: Targeted intervention will result in a greater pre- to post-intervention reduction of UE motor 
impairment when compared to non-targeted intervention. Approach: This is a prospective double-blind RCT with 
parallel arm design. 130 individuals with mild, moderate, and severe post-stroke UE hemiparesis will be enrolled. 
Subjects within each impairment level will be randomly assigned to either a targeted or non-targeted treatment 
group for 2 hr rehabilitation sessions 3x/week for 4 weeks (a total of 12 sessions). Targeted practice is defined as 
a treatment targeted at specific UE motor deficits characterizing each UE impairment level enabled by our original 
measurement method. Non-targeted practice is a standard of care treatment that consists of task practice with no 
guidance from measurement to choose appropriate tasks or address specific underlying deficits. 
 
Aim # 2: Determine critical neuromechanical factors influencing response to targeted or non-targeted therapy 
 
Hypothesis: Response to targeted therapy will be associated with recovery of more normal UE movement and 
muscle activity patterns. Approach: Our measurement framework successfully allows us to target therapy. 
However detailed neuromechanical analysis is critical for documenting the baseline status of motor control 
process in order to quantify treatment-related changes in these processes. Multiple regression models will be 
used to determine the influence of pre- to post-intervention changes in neuromechanical factors and UE motor 
impairment as measured by the Rasch FMA-UE change score. This knowledge will enable further refinements of 
existing treatments and facilitate development of new treatments to target underlying factors.  
 
 
Medical University of South Carolina 
Protocol 

 
 
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Aim #3: Determine critical predictors of the time-course of response to rehabilitation. 
 
Hypothesis: People with stroke have different patterns of recovery; key neuromechanical variables predict these 
patterns. Approach: Growth mixture modeling (GMM) will be applied to longitudinal Rasch FMA-UE measures. 
GMM separates a sample into subgroups of people showing similar recovery patterns, and specifies 
neuromechanical factors predicting these patterns. Using GMM within our measurement framework is a highly 
innovative method to identify distinct groups with similar recovery trajectories and describe each group’s behavior 
in terms of FMA-UE items that can/cannot be performed over the time course of treatment.   
 
 
B. BACKGROUND AND SIGNIFICANCE_________________________________________________________ 
 
Each year over 795,000 individuals in the USA have a stroke.1 Stroke causes brain cell damage or cell death 
which then leads to altered patterns of connectivity in cortical and sub-cortical neural networks supporting 
movement.2 Over 75% of stroke survivors experience some degree of upper extremity (UE) paralysis.3 
Unfortunately, UE motor function rarely recovers completely; 85% of those who survive stroke report residual 
arm/hand motor impairment severe enough to interfere with performance of daily tasks at 4 years post-stroke.4  
Recent progress in neuro- and rehabilitation science has advanced the understanding of the potential for neuronal 
recovery after stroke-related brain damage.5 These advances stem from investigations of the brain’s natural 
“plasticity” or propensity to organize/reorganize.6,7  Neural plasticity is the mechanism by which the brain encodes 
experience and learns new behaviors, and is also the mechanism by which the damaged brain relearns lost 
behavior in response to rehabilitation.8 A growing body of experimental evidence in animal models of stroke and 
translational studies in humans have shown that the amount of practice and skill training are fundamental aspects 
of rehabilitation that drive recovery.9  
2a. Amount of practice is a critical component of effective UE rehabilitation 
In the healthy nervous system, repetitive use of a limb induces plasticity of neuronal structures and networks 
within regions supporting motor control.9-11 Animal models show altered motor representations, dendritic 
branching, increased synapse growth and more efficient synaptic responses throughout motor cortical areas 
corresponding to repetitively practiced movements, suggesting possible mechanisms of use-dependent neural 
reorganization.7,12,13 In healthy humans, extensive practice of specific UE movements alters cortical motor 
representations, such that the territory representing the practiced movement expands, while territories 
representing non-practiced movements do not expand or shrink.14,15   
Similarly, repetitive use of a limb after a brain lesion promotes neural reorganization of damaged networks. In rat 
and primate models of cortical stroke, UE limb motor representation loss was prevented and cortical 
reorganization was promoted with extended task-practice.16,17 In humans with stroke, imaging studies show that 
task-practice rehabilitation programs increase the excitability of the damaged hemisphere, alter motor cortex 
topology, and contribute to the restoration of balanced inter-hemispheric facilitation and/or inhibition.18 Repetitive 
use of the more affected UE may “force” activation of neural circuitry that the patient is not using, or only 
minimally using, thereby inducing reorganization or strengthening neural adaptations that in turn enhance the use 
of that circuitry and the behavior(s) dependent upon it.  
2b. Skill training is a critical component of effective UE rehabilitation 
The greatest neuroplastic changes in cortical areas supporting UE motor control are associated with the repetition 
of new skills rather than repetition of existing skills.16 In a classic series of studies Plautz and Nudo showed that 
training a primate to retrieve a food pellet using a novel pattern of forelimb and digit coordination increased the 
size of cortical representational areas for the trained limb.11,19 In contrast, repeating an already-known limb 
coordination pattern to retrieve the pellet did not alter the movement representational area. Other studies have 
shown that skill training results in reorganization of movement representations within the motor cortex,20 
endurance training induces angiogenesis but does not alter movement representations,21 and strength training 
alters spinal motor neuron excitability but does not alter motor map organization.22 These findings imply that the 
type of tasks practiced impart structural and functional adaptive reorganization across the motor system which are 
dependent on the content of the practice sessions.  

 
 
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Accumulated evidence linking skill-training to neural plasticity has led to modern “task-oriented training” 
rehabilitation approaches.23 In a task-oriented approach, a patient is challenged to accomplish a specific goal 
(e.g., pick up and drink from a soda can) thereby engaging the patient’s visual, perceptual, cognitive and motor 
systems as he/she problem-solves how to achieve the goal.24 Each practice trial provides information to the 
patient (feedback) which forms the basis for strategizing the next attempt.25 Applied to stroke rehabilitation, the 
approach assumes learning-dependent functional recovery which is measured in terms of the patient’s ability to 
perform a specific task. For example, several large randomized controlled clinical trials have shown that high-
dose repetitive task-oriented practice improves a patient’s perceived ability to use his/her affected UE for daily 
tasks.26-28  
2c. The specific treatment effects of repetitive task-practice UE rehabilitation are not clear 
Although task-oriented approaches are efficacious, the specific effects of the treatment on motor control 
processes supporting task performance are not clear. For example, a large clinical trial of constraint induced 
movement therapy, a type of task-oriented training, enabled participants to perform tasks faster. 28 Yet the 
outcome measures used in the trial do not provide data on how participants accomplished the tasks.  
There are very few studies investigating the effects of task-oriented treatments on specific motor behaviors and/or 
underlying mechanisms. Those studies that have been conducted provide conflicting results. On the one hand, 
studies have shown the therapy improves underlying motor control strategies thereby enabling more efficient 
motor planning.29,30 On the other hand, studies have shown the therapy exaggerates compensatory movement 
patterns thereby reducing movement efficiency31,32 and possibly interfering with longer-term recovery.33,34 
Knowledge of how motor behaviors and/or neuromechanical factors are affected by treatment is key for 
establishing clear guidelines about the treatment, i.e., for which patients it is optimal, and for which patients it is 
not optimal.   
Current neurorehabilitation practice guidelines direct therapists to implement task-oriented training but the lack of 
knowledge regarding treatment effects may limit this implementation.35,36 In order to determine the most 
appropriate treatment strategy for a given patient a therapist must 1) clearly define specific UE movements that 
patient can/cannot perform, 2) determine the impact of underlying factors on his/her performance, and 3) plan an 
expected time-course of treatment. To do this, a therapist must have an assessment of UE motor function that 
reflects contemporary theoretical expectations of deficit and recovery by clearly identifying where the patient is in 
the UE recovery process and specifying the expected next steps in recovery.37 Without this information, a 
therapist is unable to tailor a repetitive task-oriented training approach to the needs of his/her patient. 
Unfortunately many assessments widely used in stroke rehabilitation are not useful for this purpose because their 
score is not meaningful.  
For example, the Fugl-Meyer Upper Extremity Assessment (FMA-UE) is the most commonly used tool used to 
measure post-stroke UE motor impairment in rehabilitation research studies.38,39 The FMA-UE is scored by 
assigning each item an ordinal rating (0=unable to perform, 1=partial performance, 2=near normal performance), 
then summing item ratings for an aggregate score. However the sum score does not reveal how an individual 
performs on specific items. What does it mean for a patient to receive a 30 on the FMA-UE? Is the client able to 
extend his/her elbow? Is s/he able to keep the elbow in full extension while elevating the shoulder to 180 
degrees? These are important questions because judgments regarding impairment severity, interpretations of 
treatment effects or response to therapy and, most importantly, decisions about treatment rely in a clear 
understanding of what a FMA-UE score means.40 
2d. Rasch measurement theory improves the meaning of the FMA-UE score 
A person’s rating on an assessment item is an interaction of the person, given his/her skill level, and an item 
which has a level of difficulty.41 Item Response Theory statistical methods such as the Rasch measurement 
model connects person-ability to item-difficulty thereby linking a score to a description of item performance.42 We 
applied the Rasch model 43 to FMA-UE data obtained from 512 persons with stroke.44 The analysis calibrated 
measures of item-difficulty and person-ability to the same metric and arranged items according to difficulty (less to 
more difficult) and persons according to ability (less to more ability). Through Rasch measurement, FMA-UE 
items represent difficulty makings along the continuum of the instrument’s construct (UE motor ability). The 
placement of person-ability on this measurement continuum enables a person’s location along the measurement 
metric, i.e., a person-ability measure, to reflect the “amount” of the construct, UE motor ability that he/she exhibits.  

 
 
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This Rasch analysis was the basis for developing a classification system which formed groups of patients having 
similar amounts of UE motor ability. In ongoing work funded by Dr. Woodbury’s CDA-2 (see Table 1, and 
Preliminary Studies) item response theory staging methods45 were applied to the Rasch FMA-UE item difficulty 
hierarchy to establish 3 stages of UE motor impairment; mild, moderate, and severe. Stages can be understood 
as several hierarchic levels along the continuum of a construct. To avoid confusion with the classic “Brunnstrom 
Stages”46 we will refer to ability levels or categories instead of stages. Cut score values were determined from 
FMA-UE items corresponding to evidence-based milestones marking a progression of post-stroke UE recovery; 
concurrent shoulder flexion/elbow extension,47 and wrist flexion/extension while keeping the proximal joints still.48  
The idea of partitioning post-stroke UE recovery into stages is not new. In 1951 Twitchell described a predictable, 
stepwise course of post-stroke UE recovery.49 Brunnstrom, furthering Twitchell’s work, mapped a sequential 6-
stage recovery process beginning with flaccidity (stage 1), advancing to proximal gross whole arm synergistic 
movements (stage 3) and onto recovery of distal isolated fine motor coordination (stage 6).46 Fugl-Meyer applied 
a numeric rating scale to Brunnstom’s taxonomy thereby echoing her stages in the FMA-UE item order.39  
The progression of FMA-UE items reflected in the progression of UE impairment levels differ from the classic 
Brunnstrom stages in content and meaning. Rasch analysis of the FMA-UE challenged the assessment’s 
construct validity and item-difficulty order (see Preliminary Studies).44  The Rasch FMA-UE item-difficulty order 
provided a framework to interpret contemporary data providing evidence that  arm movements are easier or more 
challenging based on the inherent task-specific computational demands of a movement task.50  
We argue that this Rasch FMA-UE measurement framework is a valuable foundation for designing treatment. We 
hypothesize that for each level of UE motor impairment, the Rasch FMA-UE classification system defines task-
practice conditions that are the just-right balance between person-ability and task-difficulty and therefore provides 
a platform for designing patient-targeted therapy, investigating the specific effects of treatment and identifying 
responders/non-responders.  
2e. The Rasch FMA-UE measurement framework as the basis for designing patient-targeted UE rehabilitation  
According to the Challenge Point Framework,24 optimal practice sessions occur when a learner is challenged by 
the tasks being practiced because they are well matched to his/her ability level, i.e., neither too easy nor too 
difficult. Appropriately scaling task-difficulty to match patient-ability motivates repeated attempts and optimizes 
sensorimotor feedback.24,51 In contrast, repetition of “easy” tasks (difficulty below patient-ability) may not promote 
cortical reorganization because tasks are already known.22 Repeated attempts to perform very difficult tasks (well-
Table 1: The Rasch FMA-UE UE Impairment Categories 

 
 
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above patient-ability) may elicit altered, compensatory movement configurations which may interfere with long 
term recovery.33,34   
A Rasch FMA-UE person-measure (in contrast to a sum-score) defines individuals’ response to specific FMA-UE 
items, thus a classification system based on the person-measure specifies how ability-level members respond to 
FMA-UE items. The Rasch FMA-UE metric indicates what items (UE movements) were easy enough for patients 
with poor UE motor ability and what items were challenging enough for patients with good UE motor ability. It 
therefore forms the basis for designing optimal task-oriented practice sessions.  
For example, when a person’s ability measure matches an item’s difficulty measure then it is expected that s/he 
would have a 50% probability of being able to perform this item successfully because it represents the “just right 
challenge” for the individual. Items at this level reflect movements that the patient is expected to recover in the 
short-term, i.e., as the expected-next-steps in the post-stroke UE motor recovery process. Therefore these items 
(movements) provide optimal challenge and should be targeted in task-practice sessions. A person has a greater 
than 50% probability of accomplishing items with difficulties below the person measure (“easy” items). Items at 
this level reflect movements that have already recovered and therefore do not need to be practiced in task-
practice sessions. A person has a less than 50% probability of accomplishing items with difficulties above the 
person measure (“hard” items).  Items at this level reflect movements that are too difficult for the patient at his/her 
current level of ability. As the patient recovers, these items may indicate appropriate goals for future task-practice 
sessions.  
2f. Determining neuromechanical influences on UE recovery 
One purpose of the present proposal is to explore the neuromechanical mechanisms contributing to post-stroke 
UE recovery. There is evidence supporting the hypothesis that several neuromechanical (i.e., kinematic and 
electromyographic (EMG)) factors are key to recovery. Individuals with stroke demonstrate reduced voluntary 
elbow extension range of motion52 which may be at least partially explained by abnormal elbow muscle co-activity 
between biceps and triceps. 53 Together, these impairments contribute to reduced ability make smooth reaching 
movements throughout the workspace.54 Given this limitation, people with stroke recruit the trunk as an extra 
degree of freedom.54 Anterior trunk flexion is used in place of elbow extension for reaching movements. UE motor 
recovery is characterized by improved elbow extension,55 reduced anterior trunk motion,56 and reduced muscle 
co-activity.57 
Here we aim to investigate the influence of neuromechanical mechanisms contributing to the treatment related 
changes in participants’ Rasch FMA-UE person ability measure. By investigating the relationship of 
neuromechanical factors to a person’s FMA-UE measure, we will learn more about what neuromechanical factors 
or mechanisms underlie a person’s location within this classification system. As noted in the brief literature review 
above, several studies relate neuromechanical factors to UE recovery. But in these studies, UE recovery is 
defined in terms of performance of a single task (e.g., reach-to-point) or in terms of a patient’s aggregate score on 
an assessment. Here, our measurement framework enables us to investigate how neuromechanical factors 
influence re-acquisition of the underlying construct “UE motor ability” which is defined in terms of specific FMA-UE 
items that a patient could/could not perform prior to rehabilitation but gained the ability to perform after 
rehabilitation.  
2g. The time-course of UE recovery 
Identifying and describing those that respond and do not respond to rehabilitation treatment is a growing area of 
interest in rehabilitation science. Here we aim to differentiate patterns of recovery in our sample by integrating 
Growth Mixture Modeling (GMM) into our Rasch FMA-UE measurement framework. This is a highly novel method 
for defining responders and non-responders. Although well established in educational and psychological 
literature, GMM is a new to rehabilitation science and has been used in only a few stroke rehabilitation studies to 
date.55,58,59   
GMM offers a robust method of identifying subgroups of people with stroke who follow distinct trajectories of UE 
recovery. In contrast to analyses that focus on mean-level change in a sample, GMM elucidates how different 
people recover in different ways. GMM separates repeated measurements of a sample into groups of individuals 
showing similar patterns of change over time. In addition, the analysis specifies factors predicting these distinct 
patterns. When placed into the Rasch FMA-UE measurement framework, the results of the GMM analysis will 

 
 
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enable a clear description of each subgroup because the subgroup’s pattern of UE recovery will be directly 
connected to a description of the specific FMA-UE items that can/cannot be performed.   
2h. Pilot study: targeted-rehabilitation versus non-targeted rehabilitation  
 Our recent pilot work32 provides evidence that a targeted rehabilitation intervention maximizes UE motor function 
when compared to non-targeted intervention. We conducted a pilot study (n=12, with 6 subjects per intervention 
group) which investigated the effects of an intervention targeted at participants with moderate post-stroke UE 
motor impairment, specifically those individuals who displayed reduced shoulder-elbow interjoint coordination and 
excessive anterior trunk flexion. The intervention 
was “targeted” meaning that it afforded opportunity 
for participants to practice a more normal reaching 
pattern characterized by concurrent shoulder 
flexion-elbow extension while cueing participants to 
avoid using excessive anterior trunk flexion. The 
trunk cue was proved with a trunk restraint that was 
loosely fit across the subject’s chest. Participants 
were randomly assigned to a high-intensity task 
practice group with trunk restraint (targeted) or a 
high intensity task practice group without trunk 
restraint (non-targeted). Both groups were matched 
on amount of time spent in therapy (4 hrs/day, over 
10 days). The FMA-UE was administered 1 week 
prior to be start of therapy, and then administered 
again within one week after the conclusion of 
therapy. Each subject’s FMA-UE was converted to 
a person-ability measure with Rasch analysis. The 
average Rasch FMA-UE measure for each group is 
shown in Figure 1. Pre-intervention, the targeted 
group scored an average of 0.90 (±1.01) logits and the non-targeted group scored a similar 0.89 (±0.74) logits. 
After the intervention subjects in the targeted group scored 2.30 (±1.0) logits while the non-targeted subjects 
scored 1.42 (±0.45) logits. These data demonstrate the feasibility of targeting an intervention at a specific UE 
motor impairment and suggest that targeted therapy holds potential for reducing UE motor impairment (as 
measured by the FMA-UE) to a greater degree than a non-targeted intervention. See Preliminary Studies for 
more information on this pilot study.  
Significance and Innovation: A modern measurement method, such as the Rasch model, presents an 
innovative way to think about measurement and treatment. We built an original post-stroke UE measurement 
framework with Rasch analysis. For the first time a methodology is available to researchers and therapists 
offering an evidence-based method to directly connect a patient’s UE motor-ability measure to a description of 
movements that can/cannot be accomplished. This connection, not only allows us to re-evaluate traditional 
expectations of post-stroke UE recovery, but also maps recovery as a progression of item difficulties. The 
progression of item difficulties provides a basis for interpreting and/or elucidating emerging data about post-stroke 
UE impairment and recovery. Moreover, the framework provides an innovative platform to determine the influence 
of neuromechanical factors on recovery of specific motor behaviors and determine how these specific motor 
behaviors evolve over time. No similar measurement framework exists. Indeed, standardized assessments have 
offered the practicing clinician little benefit for making day-to-day clinical practice decisions. By restructuring the 
FMA-UE with Rasch analysis, we anticipate that the framework will provide a tool for therapists to make 
theoretically-grounded clinical decisions, set patient-tailored goals, plan optimal treatment, and clearly monitor 
patient progress. We anticipate that the aims of the present study, if successfully achieved, will lead to 
refinements of existing interventions in order to more accurately target critical underlying impairments and 
patterns of recovery. In addition, the investigation will be a tool for future investigations of therapy targets and 
novel interventions as of yet unconsidered.  Efforts such as these may show promise for closing the gap between 
research and practice in rehabilitation. 
 
 
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
Targeted, n=5
Non-Targeted, n=6
Average Rasch FMA-UE Person Measure 
(Logits)
Pilot Study: Targeted vs. Non-Targeted UE 
Rehabilitation Therapy
PRE
POST
Figure 1: Rasch FMA-UE measure pre- and post-
treatment 

 
 
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C. PRELIMINARY STUDIES___________________________________________________________________ 
 
3a. Development of the Rasch FMA-UE measurement framework 
In published research44 we restructured the FMA-UE to reflect a progression of UE motor recovery typically seen 
in individuals with stroke thereby challenging the traditional reflex-hierarchical theoretical construct of post-stroke 
UE recovery underlying the assessment.39  We applied the Rasch polytomous measurement model43 to FMA-UE 
data obtained from 512 individuals, ages 69.8±11.1 years, 0–145 days post-stroke. Factor loadings and item infit 
statistics suggested that the three reflex items were empirically disconnected from other assessment items. The 
reflex items were removed. 
The analysis simultaneously calibrated measures of item-difficulty and person-ability to the same metric and 
arranged items according to difficulty (less to more difficult) and persons according to ability (less to more ability).  
The analysis illustrated what movements were able to be performed by individuals with less motor ability (i.e., 
greater impairment) and what movements were able to be performed by individuals with more motor ability (i.e., 
less motor impairment). 
The Rasch-derived FMA-UE item difficulty hierarchy is presented in Table 2. Items are ordered in decreasing 
order of difficulty so that the most challenging items are at the top of the table and least difficult items are at the 
bottom of the table.  Item difficulty calibrations are given in the middle column (measure) along with the standard 
error of the measure in the right column. This item order was consistent in 98% of the 512 person sample in this 
study. In a subsequent study we showed that it was invariant in 377 people tested across two time periods.60 
The FMA-UE item difficulty order is not entirely consistent with the traditional recovery model because items do 
not progress in a strict synergistic-to-isolated, proximal-to-distal order. For example, Table 1 shows that some 
proximal arm motions are located near the bottom of the 
table. These “easy” items are expected to be among the first 
motions to recover after stroke (e.g., elbow flexion, shoulder 
adduction with internal rotation). But unexpectedly, some 
distal arm motions are also located near the bottom of the 
table. They are also “easy” items and also are expected to 
recover early after stroke (e.g., finger mass flexion, cylindrical 
grasp).  
The FMA-UE item difficulty hierarchy provides a framework to 
elucidate and interpret contemporary research.  Our results 
suggest that the FMA-UE items are arranged according to 
the difficulty of motion. That is, arm movements are “easier 
“or “more challenging” based on the inherent task-specific 
demands of the movement. Elbow flexion may be “easier” 
than wrist circumduction because the movement is inherently 
less complex, i.e., requires less agonist-antagonist 
coordination. Shoulder flexion to 180 degrees with the elbow 
extended may be “difficult” because of the influence of gravity 
on a long lever arm.  
3b. Use of the framework to match person-ability to item-
difficulty 
In a separate study we aimed to illustrate the connection 
between a Rasch FMA-UE person-ability measure and FMA-UE item-difficulties. The data shown here were 
generated from Dr. Woodbury’s funded VA RR&D CDA-2 project. For this project, 55 participants (52 completed 
testing), ages 45-88 years who were an average of 7 years post first time ischemic stroke were enrolled into a 
prospective cross-sectional study of UE reaching ability.  
FMA-UE item 
Measure 
Error 
Wrist circumduction 
 1.67 
0.10 
Hook grasp 
 1.33 
0.10 
Shoulder flexion to 180°, elbow extended 
 1.26 
0.10 
Spherical grasp 
 1.20 
0.10 
Lateral prehension 
 1.08 
0.10 
Wrist flexion-extension, elbow extended 
 1.06 
0.10 
Pronation-supination, elbow extended 
 1.00 
0.10 
Wrist stable, elbow extended 
 0.95 
0.10 
Movement with normal speed 
 0.89 
0.10 
Forearm supination 
 0.65 
0.10 
Shoulder abduction to 90°, elbow extended 
 0.28 
0.10 
Movement without dysmetria 
 0.27 
0.10 
Shoulder external rotation 
 0.24 
0.10 
Wrist stable, elbow at 90°  
 0.18 
0.10 
Wrist flexion-extension, elbow at 90° 
 0.12 
0.10 
Palmar prehension 
 0.06 
0.10 
Scapular retraction 
 0.03 
0.10 
Pronation-supination, elbow at 90° 
-0.17 
0.11 
Shoulder flexion to 90°, elbow extended 
-0.21 
0.11 
Hand to lumbar spine  
-0.40 
0.11 
Shoulder abduction  
-0.56 
0.11 
Elbow extension  
-0.64 
0.11 
Forearm pronation  
-0.87 
0.11 
Movement without tremor  
-0.91 
0.11 
Cylindrical grasp 
-1.10 
0.12 
Finger mass extension (relax flexion) 
-1.25 
0.12 
Scapular elevation  
-1.40 
0.12 
Finger mass flexion  
-1.44 
0.12 
Shoulder adduction with internal rotation 
-1.56 
0.12 
Elbow flexion  
-1.76 
0.13 
Table 2: The Rasch FMA-UE Item Difficulty 

 
 
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Figure 2, a Rasch FMA-UE person-item map, presents the sample ability (n=52) measured on the same metric 
as item difficulty in order to illustrate the link between person-ability and item-difficulty. The column of numbers to 
the left is the measurement metric (logits). The center line represents 
the FMA-UE’s latent trait, UE motor ability. The “x” symbols to the left of 
the center line represent each participant’s person ability measure. 
Items are displayed to the right of this line. The map is arranged so that 
the most able people and the most difficult items are at the top and the 
least able people and least difficult items are at the bottom. A curve 
representing the distribution of the sample’s UE motor ability has been 
overlaid onto the figure to illustrate the relationship of the sample’s 
ability to assessment’s item-difficulties. The location of each item on the 
metric corresponds to its average difficulty across all categories, that is, 
the item difficulty measure in Table 2. However, item difficulties actually 
range over the metric because each item has a rating scale. The dotted 
rectangular box surrounding items illustrates this range.  
When a person’s ability measure matches an item’s difficulty measure 
then it is expected that s/he would have a 50% probability of being able 
to perform this item successfully because it represents the “just right 
challenge” for the individual. A person has a less than 50% probability 
of accomplishing items with difficulties above the person measure 
(“hard” items) and a greater than 50% probability of accomplishing 
items with difficulties below the person measure (“easy” items). 
The item map illustrates the concept that successful performance of 
more difficult items requires a greater “amount” of UE motor ability. As 
seen on the item map, persons with low FMA-UE scores were likely to 
exhibit control of 1 joint (e.g., items at the bottom of the figure such as elbow flexion or shoulder adduction); 
persons with higher scores were likely to exhibit control of multiple joints (e.g., items at the top of the figure such 
as shoulder flexion to 180 degrees, wrist circumduction). The map suggests that UE motor recovery corresponds 
with an increased probability of performing tasks requiring synchronous control of agonist-antagonists to 
overcome gravity, rotate joints or achieve dexterous prehension patterns.  
3c. Use of the framework to link measurement to rehabilitation treatment design 
In a recent publication61 we demonstrated a method to link a Rasch FMA-UE person-ability measure to a patient-
specific rehabilitation treatment plan. The data shown here were generated from Dr. Woodbury’s funded VA 
RR&D CDA-2 project.  
Figure 3 presents a Rasch FMA-UE Keyform Recovery Map. A keyform looks similar to a survey questionnaire 
with the items of the survey on one side of the form and numbers corresponding to the rating scale of each item, 
placed on the other side of the form. While the keyform is similar to a survey questionnaire, it has two additional 
features. First, the items of the assessment are ordered on the basis of Rasch item-difficulty calibrations. The 
items progress from the easiest item on the bottom of the form to the hardest items on the top of the form. 
Second, the ratings for the items are not lined-up in straight vertical columns as on a typical survey. Instead each 
rating for each item is associated with a difficulty calibration. Item ratings stair-step from left to right to correspond 
with increasing amounts of person-ability required to perform more difficult items. The form enables one to view 
the specific items that a client can or cannot perform. This information can assist a therapist to tailor treatments to 
a client’s individual ability-level. 
To illustrate the use of a keyform, one individual with moderate UE motor impairment (defined by the Rasch FMA-
UE impairment categories) enrolled in Dr. Woodbury’s CDA2 was randomly selected. This person’s performance 
on each FMA-UE item is displayed on the keyform.  Item ratings show a pattern of what the client can do, can 
partially do, and cannot do. This individual shows near normal performance (rating of “2”) on five of the six easiest 
items and partial performance (rating of “1”) on four of the nine of the most difficult items. The area boxed by the 
dashed-line in the figure (i.e., items from movement without tremor to forearm supination) illustrates the “transition 
zone” where the client’s performance fluctuates between partial performance (rating of “1”) and near normal 
performance (rating of “2”).  This transition zone can be the basis for goal setting and treatment planning. 
     6               | 
                     | 
                     | 
                     | 
    5           X   T+ 
                     | 
                     | 
                X    | 
                     | 
    4                + 
               XX    | 
              XXX    | 
                     | 
               XX    | 
    3                + 
                X   S| 
                     | 
             XXXX    | 
                     | 
    2                +T 
                     | 
                X    |  Wrist circumduction 
              XXX    |  Hook grasp 
                X    |  Shoulder flexion to 180  
Spherical grasp 
    1          XX    +S Lateral prehension  
 
Wrist flex-ext elbow ext. 
    Forearm pro-sup elbow ext. 
Wrist stable elbow ext.  
                     |  Movement with norm speed 
            XXXXX   M|  Forearm supination 
            XXXXX    | 
               XX    |  Shoulder abduction to 90 
Movement without dysmetria 
    Shoulder external rotation 
Wrist stable, elbow bent 
    Wrist flex-ext elbow bent 
    0         XXX    +M Palmar prehension 
 
Scapular retraction 
                X    |  Forearm pro-sup elbow bent 
Shoulder flex to 90 
                     |  Hand to lumbar spine 
                X    |  Shoulder abduction 
 
Elbow extension 
               XX    |  Forearm pronation 
   -1                +S Movement without tremor 
Cylindrical grasp  
              XXX    |  Finger mass ext (relax flex) 
                X   S|  Scapular elevation 
 
Finger mass flexion  
                     |  Shoulder adduction 
              XXX    |  Elbow flexion 
   -2                +T 
                X    | 
               XX    | 
                     | 
                     | 
   -3                + 
                     | 
                     | 
                    T| 
                     | 
   -4           X    + 
                     | 
                     | 
                     | 
                     | 
   -5                + 
                X    | 
                     | 
                     | 
                     | 
   -6                |              
Figure 2: Rasch FMA-UE person-

 
 
9 of  33 
Because items in the transition zone are at the “just right challenge” for the individual, the position of items in 
relationship to this zone reflect the client’s expected next steps in the post-stroke UE motor recovery process.  
Motor behaviors (items) within the lower parts of the transition zone may suggest appropriate shorter term 
functional goals, while motor behaviors (items) within the upper parts or well above the transition zone may form 
the foundation for appropriate 
longer term functional goals.  
3d. The Rasch-derived FMA-
UE impairment categories 
The purpose of this ongoing 
work is to build a 
classification system 
depicting how people with 
various levels of UE motor 
impairment (severe, 
moderate, mild) interact with 
FMA-UE items. The data 
shown here were generated 
from Dr. Woodbury’s funded 
VA RR&D CDA-2 project.  
Item response theory staging 
methods45,62,63 were used to differentiate 3 levels of UE motor impairment; severe, moderate and mild. Table 3 
presents the Rasch FMA-UE Keyform Staging Chart.  Rows of FMA-UE items are listed in order of decreasing 
difficulty level. The 3-point rating scale for each item is presented to the left of each item label. The blue shaded 
bars designate each item’s “0” rating, 
grey shaded bars designate the “1” 
rating, and green shaded bars designate 
the “2” rating. The numbered scale at the 
top and bottom of the chart represents 
the “amount” of the underlying construct, 
UE motor ability, progressing from less 
ability (left) to more ability (right) and 
measured in log-equivalent units (logits). 
As item difficulty increases, the rating 
scale stair-steps to the right to illustrate 
the concept that more UE motor ability is 
required to accomplish more difficult 
items. Three cut scores (vertical lines) 
divide the FMA-UE scale into 3 
impairment levels. 
Cut-scores marking boundaries between 
UE impairment levels were based on an 
extensive literature review to identify a 
sequence of critical milestones marking post-stroke UE recovery; the ability to (1) simultaneously flex the shoulder 
and extend the elbow,47 and  (2) rotate the distal forearm while keeping the proximal joints still.48 We identified 
FMA-UE items corresponding to the critical milestones then calculated Rasch-Andrich step thresholds43 to mark 
boundaries between categories. Threshold values correspond to the vertical lines in the figure; the threshold 
marking the transition from severe to moderate = -0.12 logits, and from moderate to mild = 2.44 logits.  
 
This classification system defines UE motor behaviors characterizing each impairment level. Characteristic 
behaviors are illustrated by the expected FMA-UE item ratings for each stage’s column in the figure. For example, 
people classified in the FMA-UE “severe” category are partially able to accomplish (grey shaded bars) elbow 
flexion, scapular elevation, shoulder adduction, mass finger flexion and more difficult movements such as 
Figure 3: Rasch FMA-UE Keyform Recovery Map
Table 3: Rasch FMA-UE Keyform Staging Chart 

 
 
10 of  33 
shoulder abduction, elbow extension, shoulder flexion, forearm pronation/supination. They will be unable to 
perform (blue shaded bars) all other items. Initial reacquisition of the ability to simultaneously flex the shoulder 
while extending the elbow (transition from scoring 0 to scoring 1 on the corresponding FMA-UE item) marks entry 
to the next category. People in the “moderate” category have near normal ability (expected score =2, green 
shaded bars) on items addressing elbow flexion, scapular elevation, finger flexion, relaxation of a tight fist. They 
should have partial ability (grey shaded bars) items addressing shoulder flexion to 90 degrees while keeping the 
elbow straight, external rotation, individual finger movements and some prehension skills. People in the “mild” 
category will exhibit “2” on the majority of items (green shaded bars) but may have partial ability (grey shaded 
bars) to perform the most difficult items such as wrist circumduction and hook grasp. The results of this analysis 
are also summarized in Table 1. 
3e. Kinematic and EMG findings to validate the Rasch-derived FMA-UE impairment categories 
The purpose of this ongoing work is to validate the Rasch FMA-UE impairment categories with neuromechanical 
analyses. The 55 person sample enrolled in Dr. Woodbury’s CDA2 study was divided into subgroups according to 
the FMA-UE impairment category definitions described above. Extensive kinematic, EMG analyses were 
conducted while subjects performed 5 repetitions of an unrestrained reach-to-grasp task at a fast pace.  
Figure 4 presents angle-angle 
plots. Panels A-C in red present 
kinematic data from 3 
representative individuals with 
stroke. The rightmost panel in 
blue presents kinematic data 
from a neurologically healthy 
individual.  Elbow extension (x-
axis) is plotted with shoulder 
flexion (y-axis) for the 4 
individuals. Person A (left 
panel) has severe UE motor 
impairment as evidenced by 
utilizing approximately 20 degrees of shoulder flexion and virtually no elbow extension during the task. Person B 
(middle panel) with moderate impairment utilized approximately 40 degrees of shoulder flexion, and 20 degrees of 
elbow extension. Person C (right panel) with mild impairment utilized approximately 40 degrees of shoulder 
flexion and 45 degrees of elbow extension during the task. The performance of Person C, the mildly impaired 
individual is similar to the healthy individual whose data is presented in the rightmost panel. The healthy individual 
utilized approximately 70 degrees of shoulder flexion and 80 degrees of elbow extension to accomplish the task.  
We tested the hypothesis that the groups formed by the Rasch 
FMA-UE impairment categories differed according to (1) elbow 
active range of motion (AROM), (2) hand path curvature (HPC), and 
(3) muscle onset.  These neuromechanical variables were chosen 
because they measure critical aspects of motor control. Elbow 
active range of motion measures the ability to execute a goal 
directed movement, HPC is a surrogate measure of shoulder-elbow 
interjoint coordination, and muscle onset indicates the activation of 
key agonistic and synergistic muscles, thus indicates the integrity of 
descending motor tracts and motor neurons. Neuromechanical 
variables were averaged for the 5 trials, and compared with ANOVA 
and Tukey’s HSD post-hoc comparisons with significance defined 
as p<0.05.  
Figure 5 presents elbow AROM (y-axis) averaged for each FMA-UE impairment category (x-axis). Elbow AROM 
is shown as a percentage of normal range of motion. As expected, and consistent with Figure 4 above, those with 
severe UE impairment exhibited the lowest elbow AROM and those with mild impairment exhibited more normal 
elbow AROM. Post-hoc pairwise comparisons were all statistically significantly different (all comparisons p<0.05).   
Figure 4:  Angle-angle plots (red= stroke, blue = healthy) 
Figure 5: Elbow active range of motion 

 
 
11 of  33 
Figure 6 illustrates HPC (y-axis) averaged for each FMA-UE impairment category (x-axis). HPC was calculated 
as a ratio of the distance that the lateral wrist marker 
actually traveled to the target divided by the most direct 
distance between the hand and target at the beginning of 
movement. More direct, efficient paths have values close to 
1. Higher values indicate more curved hand path 
trajectories. The variable is a surrogate measure of 
shoulder-elbow interjoint coordination such that healthy 
individuals who exhibit normal shoulder-elbow coordination 
demonstrate HPC values near 1. As expected, and 
consistent with Figure 4 above, those with severe UE 
impairment exhibited the highest HPC values which 
indicated impaired shoulder-elbow coordination. Those with 
mild impairment exhibited more normal HPC values. Post-
hoc pairwise comparisons were all statistically significantly 
different (p<0.05) except for the comparison between the 
moderate and mild categories (p=0.07).   
Figure 7 illustrates muscle onset (y-axis) averaged for each FMA-UE impairment category (x-axis). Muscle onset 
(msec) was defined as occurring prior to (positive value) 
or after (negative value) the beginning of a forward 
reaching movement for the anterior deltoid (AD) and 
infraspinatus (IS) muscles. The AD is an agonist, and the 
IS is a synergist for the movement. The threshold of 
muscle onset was defined as 4 standard deviations 
above resting muscle activity. Movement onset 
(represented by the line at 0.00) was defined as the time 
point at which the linear velocity of the lateral wrist 
marker exceeded 5% peak velocity. A negative value 
indicates delayed activation; a positive value indicates 
anticipatory activation.  The figure shows that the 
activation of the AD and IS are delayed for individuals in 
the severe and moderate categories. People in the mild 
category exhibit delayed AD, but are able to activate IS in 
an anticipatory manner, similar to healthy individuals. 
Post-hoc pairwise comparisons indicated significant 
differences between severe and mild (p=0.001) 
individuals, but all other comparisons were not significant.   
3f. Pilot tested targeted vs. non-targeted rehabilitation for one UE impairment category 
In published research32 we conducted a pilot study to establish feasibility of our patient-targeted UE rehabilitation 
approach. We enrolled 12 individuals with stroke, 6 to each of two UE rehabilitation interventions. One 
intervention was targeted at the movement deficits of people with moderate stroke, the other intervention did not 
specifically target movement deficits but instead promoted overall arm-use.  
We first utilized the Rasch FMA-UE to describe specific motor abilities of the sample and documented that 
individuals with moderate UE motor impairment fluctuate between partial ability and near normal ability to perform 
movements requiring simultaneous control of two joints. For this group of individuals, a key motor behavior 
marking an expected next step in the recovery process is the ability to simultaneously 
control two joints while moving a third. Therefore, we designed an intervention to match 
the ability level of this category.  
The targeted-training group performed all task-practice sessions behind a trunk restraint 
that prevented anterior trunk motion (see photo to left). Tasks for this group were located 
to afford repeated use of a shoulder flexion-elbow extension reaching pattern. The non-targeted treatment, 
constraint induced movement therapy delivered in its signature dose, was intended to provide high-dose repetitive 
task practice but was not aimed at altering any specific movement pattern.  
Figure 7: Muscle onset 
Figure 6: Hand Path Curvature 

 
 
12 of  33 
Results from the study are presented in Figure 1 above and also Figure 8 which presents angle-angle plots for 2 
representative individuals from this pilot study. The angle-angle diagrams for two representative individuals 
illustrate the treatment results. Specifically, Subject 1 (top row), a participant in the targeted training group, 
increased his ability to make a smooth transition from elbow flexion to elbow extension in mid-reach. In contrast 
the diagram of Subject 8 (bottom row), did not alter his movement pattern following non-targeted training.  
Group data (not presented) 
suggested that participants 
demonstrated expected UE 
movement patterns prior to the 
intervention in that while 
attempting to reach forward 
they had difficulty extending the 
elbow while flexing the 
shoulder. Participants who 
underwent an intervention 
specifically aimed at altering 
this movement pattern 
demonstrated a statistically 
significant Pre to Post gain in 
voluntary elbow extension 
ranges of motion whereas 
those who underwent an 
intervention that was not aimed 
at altering the compensatory 
movement pattern showed very 
little gain in voluntary elbow 
extension. For example 4 out of 
5 participants in the targeted 
treatment group showed 
increased elbow extension 
angular excursion, while 4 out 
of 5 participants in the non-targeted treatment group showed little change in elbow extension angular excursion, 
or surprisingly increased elbow flexion angular excursion after training.  
 
D. RESEARCH DESIGN AND METHODS                                                                                                     _ 
 
Methods and Procedures for All Aims: 
Study Design: This is a prospective double-blind randomized trial with parallel arm design. 130 individuals with 
post-stroke UE hemiparesis will be enrolled. Each participant will be assigned a treatment group based on their 
Rasch analysis-derived FMA-UE score and classification system described in this proposal. That is, participants 
will be stratified into 1 of 3 levels of post-stroke UE motor impairment severity (mild, moderate, severe) based on 
our classification system.  There will be two treatment groups for each severity level; a targeted-treatment group 
and a non-targeted treatment group. Subjects within each severity level will be randomized to either targeted or 
non-targeted rehabilitation therapy for their severity level. Thus, there will be a total of 6 treatment groups.  
Sample size was calculated based on FMA-UE data obtained from our pilot study (see Preliminary Studies) to 
determine whether there is a statistical difference in people receiving targeted rehabilitation vs. a comparison non-
targeted intervention in the present parallel arm design with 6 treatment groups. Specifically, we will test Ho: µ 
targeted = µ non-targeted, versus the two tailed alternative Ha: µ targeted ≠ µ non-targeted. The pilot study 
demonstrated that the targeted (trunk restraint) group exhibited a post-training Rasch-derived FMA-UE person 
ability measure of 2.30 (±1.00) logits, while the non-targeted intervention (mCIMT) group exhibited a post-training 
Rasch FMA-UE score of 1.42 (±0.45) logits which yields a Cohen’s d effect size of 1.13. With an alpha level = 
0.05, for a two-tailed hypothesis test at a 90% power level, the sample size calculation specified that 18 
individuals are needed in each group to answer the research hypothesis confidently. With 6 treatment groups, 
Figure 8: Angle – angle plots  

 
 
13 of  33 
N=108. Based on the stroke rehabilitation literature we anticipate a 20% drop out rate and therefore will enroll 
N=130 subjects.  
Project Timeline: 
 
Recruitment: This is a VA funded study (VA Merit Award) that will enroll Veterans and non-Veterans. Therefore, 
subjects will be recruited in collaboration with two stroke clinics: (1) the Ralph H. Johnson VAMC Physical 
Medicine and Rehabilitation (PM&R) stroke services and (2) the Medical University of South Carolina (MUSC) 
Comprehensive Stroke Center.  
The Ralph H. Johnson VAMC PM&R Service coordinated the care of the 3500 veterans with stroke who were 
treated in 2007-2010 in the Charleston Veterans Affairs catchment area along the South Carolina and Georgia 
coast. There are 4 neurology follow up clinics occurring each week in which Veterans with stroke are seen. 
Investigators from the Department of Health Science and Research (the Department of Drs. Woodbury and 
Kautz) attend monthly grand-rounds at the VAMC PM&R department and therefore have developed a close 
working relationship with the neurorehabilitation therapy team. Recruitment for this study will be accomplished by 
advertisements at each VA facility in the catchment area, consultations with the PM&R staff, and presentations to 
the VA rehabilitation teams.  
The MUSC Stroke Center sees over 50 new stroke patients per month and routinely screens all patients for 
eligibility to various research studies. Their database currently contains several hundred persons with stroke who 
have agreed to be contacted for participation in research studies. Investigators from the Department of Health 
Science and Research (the Department of Drs. Woodbury and Kautz) meet weekly with the MUSC Stroke Center 
medical and research teams to discuss and plan recruitment for research studies.  
Of the 130 subjects that we will enroll, 20 of them will be asked to participate with TMS. Once 20 subjects have 
completed all testing with TMS, subject participation with this device will be concluded.  
Inclusion criteria: 1) experienced ischemic stroke at least 3 mo. prior. The lesion type and location will be 
confirmed with medical records and past MRI or CT scan. This criteria is based on evidence suggesting lesions 
located in brainstem or cerebellum64 and hemorrhagic65 stroke may affect neural reorganization and observable 
patterns of UE motor recovery differently than lesion in the MCA distribution or ischemic etiology; 2) passive 
range of motion in affected shoulder, elbow and wrist within functional limits; 3) 20-90 years of age.  Exclusion 
criteria: 1) pain in the affected UE that would interfere with movement; 2) unable to understand 3-step directions; 
3) orthopedic condition or impaired corrected vision that would alter kinematics of reaching; 4) Any implanted 
ferromagnetic object that could be displaced by a magnetic field.66; 5) a history of seizures. The study sample 
shall be inclusive of the general population of adults with stroke-related UE motor impairment without restriction in 
regard to gender, race, age, and socioeconomic status.  Every effort will be made to include women, minorities 
and indigenous populations.  
Procedure: Informed consent and all other procedures will occur in accordance with approval from the MUSC IRB 
and VAMC RR&D committee.  
Study Flow:  Figure 9 illustrates the study flow.  
 
 
Jan 
Feb 
Mar 
Apr 
May 
Jun 
Jul 
Aug 
Sept 
Oct 
Nov 
Dec 
Yr1 
Preparation and Recruitment 
Enroll 20 patients 
Yr2 
Enroll 48 patients 
Yr3 
Enroll 40 patients 
Yr4 
Complete follow-up tests 
Data analysis and manuscript preparation 

 
 
14 of  33 
Evaluation Sessions: Participants will undergo 
a total of 3 full-evaluation sessions; pre-
treatment, mid-treatment, and post-treatment. 
Each full-evaluation session will consist of 
administration of the FMA-UE according to 
standardized procedures.67 and 
neuromechanical analyses (kinematic and 
EMG) of unconstrained 3D reaching 
movements.  In addition, the FMA-UE will be 
administered at the end of weeks 1 and 3. 
The FMA-UE Rasch score will be used to 
progress treatment.  
Blinding:  All evaluations will be scored by an 
evaluator who is blind to treatment group 
assignment. Subjects will also be blinded to 
treatment group assignment. That is, they will 
not be told whether their treatment sessions 
are “targeted” or “non-targeted.”  
Procedure for Administration of the FMA-UE: 
The FMA-UE will be administered to 
participants at all evaluation time points 
according to standardized procedures. 
Administration of the assessment will be 
videotaped and scored by a blinded 
evaluator. The 3 reflex items will not be administered because our previous work showed that these items do not 
contribute to measurement of the construct “voluntary” UE motor function. FMA-UE item ratings will be converted 
to a person-measure using Rasch analysis (Winsteps68) with item-difficulty calibrations anchored to published 
values44 which will assure stable person-measure estimates. 
Procedure for Neuromechanical Evaluation: Kinematic and EMG analyses will be conducted at three time points 
(pre, mid and post).  
We have previously published our standardized procedures for neuromechanical evaluation.32 Subjects will be 
seated on a backless stool with the start posture standardized. Using their affected UE, subjects will perform 10 
trials of reach-to-grasp (or touch) a soda can which will be placed at a location equal to 80% of arm’s length at 
midline, a location affording maximum shoulder flexion and elbow extension.54 No trunk constraint or arm support 
will occur during testing. Kinematic data will be recorded with a 10-camera motion analysis system (PhaseSpace 
Inc) at a sampling frequency of 480 Hz using a marker set defined in our previous work.32 Kinematic data will be 
filtered with a 4th-order Butterworth low-pass filter (cutoff frequency of 12 Hz) then processed through a Visual 3D 
kinematic model using custom Matlab functions. Surface EMG electrodes will be applied to the center of the 
muscle bellies of the biceps (BI) and triceps (TRI) according to SENIAM procedures. The muscles are chosen 
because of their important roles as agonist (TRI) and antagonist (BI) for forward reach. Baseline EMG (16-
channel wireless system, Motion Lab Systems) values will be collected (2000 Hz) with the limb at rest in order to 
identify the ambient noise and isoelectric muscle activity signal level, then collected during reach-to-grasp 
movement. EMG data will be bandpass filtered (5 Hz – 1 kHz), demeaned, rectified and low-pass filtered with a 
fourth-order, zero-lag digital Butterworth filter (cutoff 20 Hz).   
We will use Transcranial Magnetic Stimulation (TMS) to measure Neural Excitability: TMS analysis will be 
conducted at five time points (pre-intervention, end of weeks 1,2, and 3, and post-intervention) 
Transcranial Magnetic Stimulation (TMS) is a means measuring the excitability of brain activity by generating a 
magnetic field that induces an electrical impulse into specific regions of the brain. The handheld TMS device that 
will be used in this study are two coils positioned side by side in a figure eight fashion. These coils, encased in 
plastic housing, produce a magnetic field that is only able to penetrate the outer layers of the cortex of the brain 
without causing pain or discomfort to the patient69.  
Figure 9: Study Flow 

 
 
15 of  33 
We will use TMS to measure Neural Excitability: Control of motor activity in the paretic hand is influenced by 
interhemispheric interactions between the motor cortices of the LH and NLH.70 Further, the degree of inter-
hemispheric inhibition (IHI) exerted from the Non-Lesioned Hemisphere (NLH) M1 to the Lesioned Hemisphere 
(LH) M1 is associated with the degree of motor skill using the paretic hand. The extent of transcallosal IHI has 
also been suggested as a mechanism underlying movement recovery or the potential for recovery. In healthy 
individuals, transcallosal input from the M1 ipsilateral to movement turns from inhibitory to excitatory as 
movement onset is approached.70  This does not happen in individuals who are post-stroke, i.e. transcallosal input 
from the NLH continues to inhibit the LH M1 as movement onset is approached.70   Furthermore, those with 
greater IHI tend to have poorer motor performance. From a behavioral standpoint, the extent of baseline motor 
deficit is also related to the response to rehabilitation, i.e. those with more severe deficits in UE movement tend to 
experience smaller gains in motor capacity, use, and quality of movement than those with milder baseline 
deficits.70 Thus, our primary outcome variable for neural excitability will be IHI.70  
 
Method to measure IHI: We will assess IHI in a manner similar to the paradigm used by Murase et al. 70 Using 
Brainsight Neuronavigation, two figure-of-eight shaped TMS coils connected to two yoked Magstim 200 
stimulators will be positioned over the M1 region corresponding to the hand knob in the LH and NLH hemisphere. 
A conditioning stimulus (CS) will be delivered to the NLH M1 followed 10ms later by a test stimulus (TS) delivered 
to the LH M1. Trials using paired-pulse TMS (CSTS) will be intermixed with trials of TS only. IHI will be 
calculated as the MEP amplitude during CSTS trials relative to MEP amplitude during TS-only trials: 
(CSTS)/TS. Ten trials of each CSTS and TS will be collected.  TMS measurements will be obtained at 5 time 
points; Pre-, end of week 1, end of week 2, end of week 3 and Post- treatment.Treatment: The Baseline Rasch 
FMA-UE person measure will be the basis for assignment to a treatment group (Targeted or Non Targeted) based 
on clients’ UE motor ability/impairment level. Within each impairment level, subjects will be randomized to a 
treatment group.  
Self-Guided Home Treatment:  Each day, the therapist will help the subject identify several daily activities that 
he/she can perform in his/her own home environment that integrate movement skills practiced during therapy 
sessions.  The therapist will, in consultation with the subject, prepare and adapt instructions for the subject to 
accomplish these activities in their own home.  This allows the therapist to integrate activities that are consistent 
with the study treatments and goals into the subject’s home environment.  Participating in the self-guided home 
treatment will reinforce the activities practiced during the study treatment sessions. The therapist will make 
periodic phone contact with all subjects during the course of the study allowing ongoing collaboration with the 
subject for suggestions and modifications to the self-guided home treatment.  Subjects will therefore have better 
access to the therapist for questions about the study, modifications to the self-guided home treatment, and study 
retention efforts. 
Dose: All subjects in all groups will engage in 12 rehabilitation sessions (3x/week over 4 weeks).. Recent data 
suggest that the dose of practice, e.g., number of movement repetitions, is important to produce neural 
reorganization and motor learning.71 We therefore will provide approximately 200 reach-to-grasp/touch repetitions 
per session which previous research has shown to be safe for people with stroke and feasible to accomplish in 2-

 
 
16 of  33 
3 hours.72 Treatment Groups: Targeted practice is defined as an evidence-based intervention targeted to specific 
UE motor deficits characteristic of persons in each UE impairment level.  Non-targeted task practice is defined as 
a “standard of care” intervention that consists of task practice with no guidance from measurement to choose 
appropriate tasks to address specific underlying deficits. Table 4 presents a summary of the treatments. 
Targeted Practice Treatment: A person with mild UE motor impairment has a 50% probability of accomplishing 
FMA-UE items requiring fine motor coordination and dexterity, i.e., items well-matched to his/her ability described 
in Table1. For people with this level of UE motor impairment Forced use task practice is an optimal evidence-
based intervention.73 Forced use therapy, like Constraint-Induced Movement Therapy28 although not delivered in 
its “signature” dose, restrains participants’ less affected UE in a glove to prevent its use thereby “forcing” 
exclusive use of the affected UE. The premise of the strategy is that repetitive object grasp, manipulation reduces 
“learned non-use”.74 The intervention is shown to improve fine motor dexterity, movement speed, and 
smoothness.31,32  
A person with moderate UE motor impairment has a 50% probability of accomplishing FMA-UE items requiring 
simultaneous control of two joints (e.g., pronate/supinate forearm with elbow extended, shoulder flexion to 90° 
with elbow extended). Task practice with trunk restraint may improve these skills. This strategy is identical to 
forced use practice except that all tasks are performed with the trunk restrained to prevent compensatory 
recruitment of trunk range of motion. Limiting anterior trunk movement enables a permissive environment (by 
reducing number of body segments requiring control) in which to practice forward reach.32,56  
A person with severe UE motor impairment has a 50% probability of accomplishing FMA-UE items requiring arm 
movement away from the body (e.g., extend elbow, flex the shoulder to 90°). Task Practice with trunk restraint 
and faded arm support requires that participants perform tasks using a trunk restraint as described above, with 
the arm supported by an overhead sling. Arm support lessens the gravitational load on the limb thereby reducing 
the “difficulty” of a reaching task and is associated with increased reach distance.75,76 
Non-targeted Standard of Care Treatment: The non-targeted intervention will be Functional Upper Extremity 
Training77, a published and standardized rehabilitation program popular among neurorehabilitation therapists and 
considered the current “standard of care.” The approach evolved from the Bobath concept but stresses the 
importance of functional activities. The approach assumes that provision of “normal” sensorimotor experiences 
will promote recovery of more normal movement patterns. Unlike contemporary motor learning approaches, 
patients are not challenged to engage in task practice independently. Instead, patients practice functional tasks 
only with the hand-over-hand guidance of the therapist.  For example, if the patient is attempting to butter toast, 
the therapist wraps his/her hand over the patients hand as patient and therapist together perform the task. 
Throughout the task the therapist provides verbal feedback to continually motivate task performance (“keep 
Table 4: Summary of treatments 
Rasch FMA-UE 
Impairment Level 
Rasch FMA-UE 
Person Measure 
Targeted Treatment 
Non-Targeted 
Treatment 
Mild 
 
>2.44 logits 
Forced-use task practice 
 
Functional Upper 
Extremity Training 
 
Moderate 
 
- 0.22 to 2.44 
logits 
 
Task practice with trunk 
restraint 
 
 
 
Severe 
 
<-0.22 logits 
 
Task practice with trunk 
restraint and faded arm 
support 
 
 
 

 
 
17 of  33 
trying!”) but does not provide specific feedback about movement quality such as joint angle or posture. Tasks are 
performed in their entirety with therapist assistance throughout.   
We will follow implementation of the therapy as per the published manual, online videos and available 
implementation guidelines. In addition, the PI recently attended an 8 hour workshop to develop competence in 
providing the therapy. We argue that Functional Upper Extremity Training77  is not a “targeted” intervention 
according to our definition. That is, the approach does not specifically target a person-ability level because there 
will be no guidance from a measurement framework from which to choose appropriate tasks to ameliorate 
underlying specific deficits. 
Specific to Aim 1: Compare the effects of targeted rehabilitation versus non-targeted rehabilitation on UE 
motor function.  
Hypothesis: Targeted intervention will result in a greater pre- to post-intervention reduction of UE motor 
impairment when compared to non-targeted intervention. 
Rationale: The Rasch-based FMA-UE classification defines levels of UE motor ability by describing UE movement 
tasks (FMA-UE items) which patients in each level can easily perform, cannot perform (too hard), and are well-
matched to ability level. This information is the basis for designing task-practice sessions to specifically target the 
patient movement abilities. Because treatment is likely to induce changes in these variables, it is reasonable to 
expect changes in participants’ Rasch FMA-UE measure. 
Approach: Dependent Variable: The dependent variable will be change in UE motor impairment as measured by 
the percent change in the Rasch FMA-UE occurring from pre- to post-intervention. The Rasch FMA-UE percent 
change will be calculated as Post minus Pre divided by Pre. 
Independent Variables: The independent variable is Group. The independent variable has two levels; targeted-
therapy and non-targeted therapy.  
 Data Analysis: ANOVA will be used to compare the mean values of the Rasch FMA-UE change scores for each 
targeted vs. non-targeted treatment group across each impairment level (mild, moderate, severe). We will correct 
for multiple comparisons, therefore, significance for all comparisons will be alpha = 0.05/3 = 0.02.  
Specific to Aim 2: Determine critical neuromechanical factors that influence response to targeted or non-
targeted therapy 
Hypothesis: Response to targeted therapy will be associated with recovery of “normal” UE movement and muscle 
activity patterns. 
Rationale: Very little is known about the neural and biomechanical mechanisms contributing to post-stroke UE 
motor impairment. Identification of the critical kinematic and neural aspects of reach contributing to changes in UE 
motor impairment occurring with therapy will permit refinement of existing and development of new interventions 
specifically targeted at improving these motor control process.  
 Approach: As described in the procedures above, we will collect kinematic and electromyographic (EMG) data to 
provide information about motor control strategies (kinematic) neural influences on motor output (EMG) 
responding to therapy.  
Dependent Variable: The dependent variable will be change in UE motor impairment as measured by the percent 
change in the Rasch FMA-UE occurring from pre- to post-intervention as calculated above.  
Independent Variables: We hypothesize that 3 independent variables will explain changes in UE motor 
impairment expected to occur with rehabilitation. These variables will be measured as the percent change in each 
variable occurring from pre- to post-intervention (post minus pre divided by pre). The variables were chosen 
because they are reasonable measures of “normal” movement based on the literature, motor control theory and 
clinical interpretation. Two kinematic variables (trunk movements, elbow extension range of motion) provide 
information about the strategy utilized to execute the movement. Trunk movement will be calculated as the 
cumulative distance a marker placed at T-10 travels during the reach. Voluntary elbow extension is calculated as 
difference between elbow joint angle at start and the joint angle at touch. One EMG variables (Biceps-Triceps co-

 
 
18 of  33 
contraction index) provide information regarding neural influences on motor output. The mean amplitude obtained 
during 5 sec. resting EMG activity will be used as baseline EMG values. For each trial, “time-to-EMG” is 
calculated as the difference between muscle onset and movement onset. Muscle onset is defined as a rise in 
EMG exceeding 4 standard deviations above resting EMG. Muscle offset is defined as a decrease in EMG below 
this value. Movement onset is defined as the time-point when velocity of the wrist marker exceeded 5% peak 
velocity. Positive time-to-EMG values indicate anticipatory muscle activation (occurred prior to movement onset); 
negative time-to-EMG values indicate delayed muscle activation (occurred after movement onset). The EMG 
activity occurring between onset and offset is defined as burst duration. A co-contraction index variable will be 
defined as Biceps Burst Duration divided by Triceps Burst Duration so that a value equal to 1 reflects 
simultaneous activity of the agonist and antagonist.  
Data analysis: Two multiple regression models will examine the relationships between the dependent and 
independent variables. One regression model will include variables from all patients involved in targeted-therapy 
(i.e., pooled data from across UE impairment levels). The second model will include variables from all patients 
involved in non-targeted therapy.  
We will first investigate assumptions of normality for all variables via visual inspection of probability plots and 
statistically verified with the Kolmogorov-Smirnov f test. If the data are not normally distributed, they will be 
logarithmically transformed.  Although we expect that all variables will be associated with the FMA-UE person-
measure, we do not expect that a simple linear trend will best describe this relationship. It is likely that the 
response variables have a different impact on the FMA-UE person-measure according the level of UE motor 
impairment. Thus it is likely that that a polynomial relationship exists between the response variables and the 
dependent variable. To determine whether a linear or polynomial regression model best fits our data we will first 
cross-plot each response variable against the dependent variable. Visual inspection of the scatterplot will help to 
facilitate the appropriate model and identify outliers which may affect the model. Outlier data points beyond 3 
standard deviations of the mean value of that variable will be inspected to determine if the data was entered 
correctly. If not, the data point will be considered an aberrant rating and dropped from analysis.  When it is 
determined that a quadratic trend likely best fits the data, we will transform the variable to its quadratic term via its 
unstandardized residual to compensate for multicolliniarity. We will then apply a general linear model regression 
procedure to the data using SAS. A forced-entry procedure will be employed in which all variables will be 
examined for each model. Adjusted R-square values, p-values and 95 percent confidence intervals will be 
calculated.  
We will test significance of the coefficient of determination (adjusted R-square value) for each response variable. 
The null hypothesis tested is that there is no significant association between each response variable and the 
dependent variable, meaning that the response variable does not contribute to UE motor ability (FMA-UE person 
measure). The alternative hypothesis is that the association is significant meaning that the response variable is 
associated with UE motor ability (FMA-UE person measure). We will reject the null hypothesis if p<0.05 which will 
lead to the conclusion that the response variable does not contribute to the FMA-UE score at a 0.05 significance 
level.  
Specific to Aim 3: Determine critical predictors of the time-course of response to targeted rehabilitation.  
Hypothesis: People with stroke have different patterns of response to therapy, some respond slowly, some 
respond more quickly. Key neuromechanical variables (baseline measurements of elbow extension, amount of 
trunk movement, and biceps-triceps muscle co-activity) predict these response patterns.  
Rationale: Individuals with different levels of post-stroke UE motor impairment likely follow distinct trajectories of 
UE recovery. It is possible that patients receiving intensive therapy make large improvements within the first few 
days of therapy, and it is also possible that some patients require days until therapy has an effect. However, little 
is known about patterns of recovery over time in response to rehabilitation. Identifying different patterns of 
recovery during therapy is critical to determine which patients may need the most extensive intervention to 
promote functional recovery, and which patients may not require intensive intervention. In addition, it is important 
to identify behavioral markers that predict gains in order to improve a-priori assessments and planning for the 
population that is most likely to benefit from an intervention after stroke. 
Approach: Growth mixture modeling (GMM) offers a robust method of identifying sub groups of people with stroke 
who follow distinct trajectories of UE recovery. In contrast to analyses that focus on mean-level change in a 

 
 
19 of  33 
sample, GMM elucidates how different people recover in different ways. GMM separates repeated measurements 
of a sample into groups of individuals showing similar patterns of change over time.  
Dependent Variable: A categorical latent variable representing unobserved groupings of stroke-patients with 
similar patterns of change in the Rasch FMA-UE scores over repeated measurements.   
Observed Variables:  The Rasch FMA-UE will be administered at 5 time periods (pre-intervention, end of weeks 
1,2 and 3 and post-intervention). The GMM calculates an intercept and slope of a line representing the mean and 
variance of the linear rate of change in Rasch FMA-UE over time. Sub-populations (or growth classes) will be 
displayed graphically. Each class will represent a percentage of the sample and demonstrate how the baseline 
Rasch FMA-UE measurement changed over time. 
Data analysis: Data from participants in targeted-rehabilitation protocols will be pooled and analyzed. Three 
models will be tested in accordance with our a-priori hypothesis that each level of impairment (mild, moderate, 
severe) should show distinct patterns of recovery, i.e., we expect 3 classes of recovery. Specifically, we will test 
whether there is one overall pattern of recovery that describes the entire sample (1-class), whether there are two 
patterns of recovery within the sample (2-class) or whether there are three patterns of recovery in the sample (3-
class). The models are not nested (a 1-class model is not a subset of the 2-class model) because different 
individuals make up each class. Therefore the chi-square model comparison test is not appropriate. Instead, we 
will define the best fitting model as the one having the lowest Bayesian Information Criteria (BIC) and an entropy 
value closest to 1.0.  
To determine the best predictors of recovery patterns we will use logistic regression to relate recovery pattern 
(growth class membership) to kinematic and EMG variables hypothesized to be important predictors of recovery. 
The predictors hypothesized to be important are baseline elbow extension AROM, amount of trunk movement, 
and muscle co-activity. The predictor variables entered into analysis will be collected pre-intervention.  Predictors 
will be examined to determine those which significantly discriminate class membership. Because the predictors 
are allowed to vary across classes, the analysis will provide a means of examining whether predictors of one 
trajectory differ across each trajectory. For example, loss of elbow extension AROM may be the most significant 
predictor of membership in one class, while inability to activate agonist muscles may be the most significant 
predictor of another recovery pattern.  
Methods specific to the SUBSTUDY 
Additionally, a group of 10 individuals with stroke will have an MRI on two visits. In order to be considered 
for this SUBSTUDY, participants will first be enrolled in the above study. The purpose of this SUBSTUDY is to 
gather preliminary data on patterns of neural activity that are associated with better performance outcomes in the 
rehabilitation intervention. We also seek to determine if the intervention is able to change baseline functional brain 
connectivity.  This is a critical piece of knowledge to have in order to accurately understand and interpret the 
primary goals of the Main study. With this knowledge we can more effectively analyze and interpret the data 
gathered from the main study.  This SUBSTUDY is non-significant risk. 
Anatomical image acquisition.  High-resolution structural scans will be obtained using an 
inversion recovery 3D spoiled gradient echo (3DSPGR) sequence using a matrix size of 256 x 
256, field of view of 24 cm, section thickness of 1.5 mm with no gap between sections, and 128 
slices, giving an in-plane resolution of 0.94 mm. This sequence will be used for anatomic overlays 
of the functional data and for spatial normalization to a standard atlas.  
Functional MRI task and acquisition.  Each participant will be asked watch a movie of hand 
movements on a monitor and mimic the ongoing actions with their own hands. Participants will be 
asked to do two, 6 min runs of the task. Each functional run consists of movement blocks 
interspersed with rest blocks. Following each rest block there will be a preparation block in which 
the participant will receive a preparation cue which counts down the number of seconds remaining 
before the motor task begins again. This preparation block will be modeled separately in the 
statistical analysis and used to eliminate the effects of attentional set-shifting to the visuo-motor 
performance data acquired in the task block. All participants performed a practice session before the functional 
MRI scan in order to limit the contribution of learning to the data acquired.  
Experiments will be conducted on a 3T MR scanner with twin-speed gradients and a birdcage head coil (3T 

 
 
20 of  33 
Siemens Trio). Whole-brain activation will be assessed by examining the blood-oxygenation-level-dependent 
(BOLD) signal by measuring changes in the T2*-relaxation rate that accompany changes in blood oxygenation 
associated with cortical activation. The images will be collected parallel to the anterior commissure-posterior 
commissure (AC-PC) line with one slice overlying the AC-PC line. Functional imaging will be performed using 
multislice gradient-echo echo planar imaging (TR=2500, TE=40 msec) with a field of view of 24 cm (frequency) 
x15 cm (phase), and an acquisition matrix of 64x40 (28 slices, 5 mm thickness, no skip). This sequence delivers 
an effective voxel resolution of 3.75 x 3.75 x 5 mm.   
Functional image analysis. Statistical parametric maps (SPMs) will be generated using SPM12 from the 
Wellcome Department of Cognitive Neurology, London, UK implemented in Matlab (The Mathworks Inc. Natick, 
MA, USA). Prior to generating SPMs, data will be preprocessed based on standard techniques. The raw data will 
be reconstructed and corrected for image distortion and alternate k-space line errors will be performed on each 
image on the basis of data acquired during phase-encoded reference imaging. The functional data sets will be 
motion corrected (intra-run realignment) within SPM12 using the first image as the reference. The functional data 
sets will be normalized to Montreal Neurological Institute (MNI) space and smoothed using an 8 x 8 x 10 mm Full 
Width at Half Maximum Gaussian smoothing kernel. The data will be modeled with a boxcar design including an 
explicit baseline model convolved with the hemodynamic response function. All data will be globally normalized 
with proportional scaling of the image means. Temporal smoothing and de-trending will be performed as part of 
the SPM analysis. SPMs will be generated using the general linear model within SPM12 for each subject. Group 
analyses will be performed using a random effects model. The random effects analysis will use the ‘contrast 
image’ generated for each subject by applying the appropriate weights to the multiple regression. The random 
effects analyses will utilize two sample t-tests available in SPM12 to compare activation patterns between groups. 
To make comparisons within groups to identify the effect of conditions, paired t-tests will be used. Secondary 
analyses will be performed on the fMRI data using a multiple regression technique. A variable, such as age, can 
be entered into the regression analysis to control for unanticipated population differences. Anatomic regions of 
interest will be defined automatically using an atlas-based program WFU_Pick Atlas, which runs in Matlab. All 
data will be thresholded at p<0.05 corrected for multiple comparisons using the false discovery rate.E. 
PROTECTION OF HUMAN SUBJECTS________________________________________________________ 
 
a.  Human Subjects Involvement and Characteristics  
 
Human Subjects Involvement and Characteristics: 130 individuals with post-stroke UE hemiparesis will participate 
in this rehabilitation research study. 
 
Participants with stroke will be recruited from three sources:  
 
(1) The Ralph H. Johnson VAMC Physical Medicine and Rehabilitation (PM&R) Service: The Ralph H. Johnson 
VAMC PM&R Service coordinated the care of the 3500 veterans with stroke who were treated in 2007-2010 in the 
Charleston Veterans Affairs catchment area along the South Carolina and Georgia coast. There are 4 neurology 
follow up clinics occurring each week in which Veterans with stroke are seen. Investigators from the Department 
of Health Science and Research (the Department of Drs. Woodbury and Kautz) attend monthly grand-rounds at 
the VAMC PM&R department and therefore have developed a close working relationship with the 
neurorehabilitation therapy team. Recruitment for this study will be accomplished by advertisements at each VA 
facility in the catchment area, consultations with the PM&R staff, and presentations to the VA rehabilitation teams. 
 
(2) The MUSC Stroke Center: The Stroke Center sees over 50 new stroke patients per month and routinely 
screens all patients for eligibility to various research studies. Their database currently contains several hundred 
persons with stroke who have agreed to be contacted for participation in research studies. Investigators from the 
Department of Health Science and Research (the Department of Drs. Woodbury and Kautz) attend weekly 
meetings with the MUSC Stroke Center medical and research teams. Therefore the two departments have a 
collaborative working relationship. We will provide our inclusion/exclusion criteria to the Stroke Center research 
team who will then pass on this information to care providers who may then refer potentially eligible patients to the 
study’s research coordinator if the patient agrees.  
(3) This study will recruit from the Registry for Stroke Recovery (RESTORE-Pro#00037803), which is a registry 
with subjects consented for future contact. RESTORE staff will query the registry for potential subjects and 
provide the Principal Investigator (PI) with the contact information of subjects who meet their criteria.  The PI or 
research staff will contact subject to further screen for potential enrollment.  
 
Sharing Data 

 
 
21 of  33 
If the subject agrees, the data collected and generated from this study will be shared and linked to RESTORE by 
the subject’s registry ID. Sharing data from this study with the registry will allow for more targeted recruitment 
efforts in the future and allow researchers at MUSC to have a more complete registry with key stroke recovery 
elements including common data and physical function characteristics that are applicable to multiple studies.  
  
 
 
 
 
Targeted/Planned Enrollment Table 
 
Total Planned Enrollment - 130 
 
TARGETED/PLANNED ENROLLMENT: Number of Subjects 
Ethnic Category 
Sex/Gender 
Females 
Males 
Total 
Hispanic or Latino 
   3 
    4 
  7 
Not Hispanic or Latino 
   48 
    75 
 123 
Ethnic Category: Total of All Subjects* 
130 
Racial Categories 
 
American Indian/Alaska Native 
0 
0 
0 
Asian 
1 
0 
1 
Native Hawaiian or Other Pacific Islander 
0 
0 
0 
Black or African American 
16 
25 
41 
White 
34 
54 
88 
Racial Categories: Total of All Subjects* 
51 
79 
130 
 
*The “Ethnic Category: Total of All Subjects” must be equal to the” Racial Categories: Total of All Subjects”.  
 
Inclusion criteria for the proposed study: 
1. Experienced a stroke at least 3 months prior that has resulted in unilateral hemiparesis. 
2. Passive range of motion in affected shoulder, elbow and wrist within functional limits; 
3. 20-80 years of age. 
 
Exclusion criteria for the proposed study:  
1. Pain in the affected upper extremity that would limit participation in the study intervention. 
2. Unable to understand 3-step directions; 
3. Unable to attend the study-related treatment or evaluation sessions 
4. Orthopedic condition in back or UE or impaired corrected vision that would alter kinematics of reaching. 
 
We expect that our sample will have demographic characteristics similar to that of the general population in this 
region of South Carolina. These percentages, based on the 2010 census, reveal that the Charleston county area 
has a population that is 64% white, 30% African-American, 1% Asian, and 5% Hispanic and Latino and 39% 
female. There will be a total of 130 individuals with post-stroke UE hemiparesis enrolled in the overall study, and 
10 subjects enrolled in this substudy.. 
 
No children will be included in this study.  
 
This project will be conducted in the Upper Extremity Motor Function Laboratory which is designated as shared 
MUSC-VA space through a formal Memorandum of Understanding between MUSC and the VA. The laboratory is 
located in the same building as the offices of the PI, Co-I, engineer and research therapy staff. 
 
 
 
Data for this study will consist of a clinical rating-scale assessment of upper extremity movement, the Fugl-Meyer 
Upper Extremity Assessment, kinematic analysis of upper extremity (UE) motion, and electromyographic (EMG) 
assessment of UE muscle activity. These data will be collected exclusively for research purposes. 

 
 
22 of  33 
 
b.  Sources of Materials 
The following information will be obtained from human subjects: Name, age, contact information, date of stroke, 
time since stroke, ethnicity, brief post-stroke medical history. Data that will be recorded from human subjects will 
include rating-scale assessments of upper extremity motor ability, kinematic motion analysis of upper extremity 
movement, measurements of upper extremity strength, and upper extremity electromyography. Identifiable 
information will be stored in password-protected files on a secure MUSC network (MUSC patients) or on the VA-
network (VA patients). All data will be coded with a unique study identifier. The only people having access to this 
identifiable information will be Dr. Woodbury and her research study staff (named on this protocol). No other 
person will have access to PHI for study participants.  All data will be de-identified with all personal identifiers 
removed for data analysis.  That is, the PHI will be stripped of its identifiers for data analysis.  Data analysis will 
incorporate only aggregate data that does not contain any participant-specific identifies. There will be no way to 
link the data being analyzed back to the individual. Hard copy data will be coded by unique study identifier and 
stored in a locked file cabinet which is located along the east wall of the secured office of the principal investigator 
which is located in room #307 of the College of Health Professions Research Building at 77 President Street in 
Charleston SC.  This space is designated as a VA research space in a VA approved memorandum of 
understanding. Once the study is completed data (described below) will be de-identified. Potential participants will 
be identified through recruiting mechanisms described above associated with the MUSC Stroke Center and VA 
PM&R service. The PI and/or study coordinator for the present study will provide the MUSC Stroke Center and 
VA PM&R service with inclusion/exclusion criteria. Personnel associated with either of these places will then 
provide our contact information to participants. Participants will then initiate contact with either the PI or Study 
Coordinator of the present study.  If potential participants meet inclusion criteria they will be asked by the study 
coordinator if they would like to participate in the current study.  If they do wish to participate, they will be 
scheduled for a time to obtain written informed consent to participate in the study.  
 
 
c.  Potential Risks  
 
Potential discomforts or risks for participation in this study are minimal. This is a prospective study with parallel 
arm design. Subjects will undergo 4 evaluation sessions (Pre-treatment, Mid-Treatment, Post-Treatment, 30 day 
Follow Up). Assessments will consist of (1) clinical rating scale assessments and (2) motion and EMG analysis. 
During both types of assessment sessions, subjects will be seated comfortably. They will be asked to perform UE 
movements commonly performed in everyday life (e.g., lift arm to eye level while keeping elbow straight, pick up a 
soda can). Sensors for motion and EMG analysis are attached to the participants’ skin. There may be a temporary 
skin reaction to the adhesive used to secure the motion analysis markers or EMG sensors to the skin. To 
minimize this, the skin will be cleaned before and after the markers or sensors are placed on the skin and 
hypoallergenic gel and tape will be used on the skin. A skin reaction is a rare occurrence and resolves within 1-2 
days. All participants will be asked if they have had any previous experience of allergic reaction to specific gel or 
tape types. If they answer yes, then we will avoid placing markers or sensors directly on the skin. Instead we will 
wrap the limb in non-sticky “pre-wrap” and attach motion sensors to it. Pre-wrap is a soft wrap often used under 
casts or braces. 
 
Subjects will be randomized to two stroke rehabilitation treatment groups; “targeted” vs. “non-targeted” and will 
engage in 12 rehabilitation treatment sessions. The only difference between the treatments is that the “targeted” 
group will receive specific instructions from the therapist regarding the participants’ quality of movement during 
rehabilitation treatment (e.g., straighten elbow, sit tall). During rehabilitation treatment, participants will be asked 
to practice using the arm most affected by stroke. They will perform 200 movement repetitions during 
rehabilitation treatment. The will include reaching, grasping and lifting common everyday objects. Participants 
may be seated or standing for these activities. While standing, all participants will be closely guarded by study 
personnel to monitor and maintain balance. In previous studies, 200 repetitions of reaching movement using the 
hemiparetic UE required approximately 2 hours with no reports of increased pain or fatigue although subjects will 
be offered a rest break after every set of 10 movements. 
 
There is a very low risk of a seizure after TMS (7 reported cases in almost 7000 studies). The risk of seizure 
induction by this protocol has been thoroughly assessed and our TMS parameters will be well within published 
safety guidelines. Of these 7 cases, none has required external intervention in the form of medications to stop the 
seizure, and no patient has had any post-seizure sequelae, nor have they developed recurrent seizures.  To 
minimize risk, we only use single pulse TMS, as the majority of adverse events have occurred after repetitive 
TMS and we will follow published safety guidelines.  Anyone with a history of seizure will not be allowed to 
participate in this portion of the study. 

 
 
23 of  33 
 
Headaches are the most common complaint from patients following treatment with TMS. In one study conducted 
by George and Belmaker (2007)78, 19% of healthy subjects reported having headaches after treatment with TMS. 
However, 17% receiving sham TMS also reported headaches after the session. These are generally self-limiting 
and respond to common analgesics like aspirin. 
 
Potential Risks of MRI:  MRI is considered minimal risk.   
1. Although the risks from magnetic resonance imaging (MRI) are low, it is critical that you do not have metal in 
the skull, metal implants, a cardiac or brain pacemaker, or old metal fragments in the eye or retina. If you/your 
child have a question about metal in your body, inform the researchers and they will determine whether it is safe 
in a MRI scan.  
2. Some discomfort may occur from having to remain still while you are in the MRI scanner. During the 
scanning you will be given an emergency ball to squeeze at any time you are feeling discomfort and desire to be 
pulled out of the scanner.   
3. The MRI scanner is noisy, and there is a risk of hearing damage if you do not wear earplugs. As stated 
above, to eliminate this risk, you will be given earplugs to wear during each scan. 
4. Although the MRI scanner is open on both ends, some people become anxious or claustrophobic when 
entering the MRI scanner due to the feeling of being enclosed. If this has happened to you in the past, inform 
the study personnel, as you/your child may be ineligible for the study. The researchers will work with you to keep 
this from happening by allowing you to view relaxing pictures on a screen prior to the start of the research 
procedure (until any anxiety has passed). Also, the researchers can talk with you during the procedure through a 
microphone in the scanner to reduce your concern. 
5. If you are female and of child-bearing potential, you must have a pregnancy test performed prior to the 
scanning procedures. This test must be negative for you to participate in the study. If pregnant you will not be 
eligible to continue in the study. 
6. Unknown Risks: The experimental procedures may have unknown side effects. The researchers will let you 
know if they learn anything that might make you change your mind about participation 
 
A licensed occupational or physical therapist will oversee all evaluation and treatment sessions. The therapist will 
monitor the participant for safety and offer rest breaks when he/she determines that the patient needs one. 
 
 
2.  ADEQUACY OF PROTECTION AGAINST RISKS  
a.  Recruitment and Informed Consent 
Subjects will be recruited in collaboration with two stroke clinics: (1) the Ralph H. Johnson VAMC Physical 
Medicine and Rehabilitation (PM&R) stroke services and (2) the Medical University of South Carolina (MUSC) 
Comprehensive Stroke Center.Recruitment and Informed Consent:  The PI (Michelle L. Woodbury) and Co-I 
(Steve Kautz) are both fully funded VA researchers. They have a collaborative relationship with the Ralph H. 
Johnson VAMC PM&R Service for patient recruitment. In addition they are both appointed in the Department of 
Health Sciences and Rehabilitation Research at MUSC. They have a strong collaborative relationship with the 
MUSC Stroke Center. The Department of Health Science and Research recruitment coordinator will be informed 
of the inclusion criteria for the present proposal.  
 
The recruitment coordinator will interface with the VAMC and MUSC for recruitment. If potential participants are 
identified that meet inclusion criteria the PI or Co-I will contact participants by phone to determine if they want to 
participate in the current study. If they wish to participate they will be scheduled for a time for the PI to obtain 
informed consent for the study proposed.   
 
Consent will be obtained by the PI after reviewing the protocol and consent form with each potential subject. If a 
potential subject is deemed unable to participate in informed consent, consent will be obtained from a relative with 
the patient present. For patients consenting themselves, every attempt will be made to have a relative present 
during the informed consent. The MUSC IRB will approve the informed consent form, and the Ralph H. Johnson 
VAMC R&D committee will also approve the protocol.  
 

 
 
24 of  33 
b.  Protection against Risk 
Potential discomforts or risks for participation in this study are minimal.  Each participant will be asked to perform 
a series of upper extremity movements that may include reaching, grasping and lifting a series of common every 
day objects. Participants may be seated or standing for these activities. While standing, all participants will be 
closely guarded by study personnel to monitor and maintain balance.  
 
There may be a temporary skin reaction to the adhesive used to secure the motion analysis markers or EMG 
sensors to the skin. To minimize this, the skin will be cleaned before and after the markers or sensors are placed 
on the skin and hypoallergenic electrode gel and tape will be used on the skin. A skin reaction is a rare 
occurrence and resolves within 1-2 days. All participants will be asked if they have had any previous experience 
of allergic reaction to specific gel or tape types. If the participant has a history of reaction to gels/tapes then the 
limb will be wrapped in non-sticky pre-wrap and motion sensors will be attached to it. Pre-wrap is a soft wrap 
often used under casts or braces.  
 
During rehabilitation treatment, participants will be asked to practice using the arm most affected by stroke. They 
will perform 200 movement repetitions during rehabilitation treatment. The will include reaching, grasping and 
lifting common everyday objects. Participants may be seated or standing for these activities. While standing, all 
participants will be closely guarded by study personnel to monitor and maintain balance. In previous studies, 200 
repetitions of reaching movement using the hemiparetic UE required approximately 2 hours with no reports of 
increased pain or fatigue although subjects will be offered a rest break after every set of 10 movements. 
 
A licensed occupational or physical therapist will oversee all evaluation and treatment sessions. The therapist will 
monitor the participant for safety and offer rest breaks when he/she determines that the patient needs one. 
 
Participants will undergo screening before the MRI. The screening form has been uploaded. This screening form 
asks questions such as “do you have any metal in your body?”, “are you claustrophobic?” If the participant 
answers “yes” to any of these screening questions, we will not obtain the MRI.  While in the MRI scanner, the 
participant will be given an emergency ball to squeeze at any time that he/she is feeling discomfort and desire to 
be pulled out of the scanner.  The participant can stop the scanning protocol at any time. All participants will wear 
earplugs to protect against possible hearing damage. A member of the research team will accompany the 
participants to the scanner and remain outside the MRI but will remain in voice contact with the subject while 
he/she is in the scanner (via a microphone). The research team member will provide reassurance, answer 
questions and coach the subject as needed. If subject is pregnant, they will not be enrolled in this substudy.  
 
All data and documents associated with this study will be coded with a unique study identifier and securely stored 
in either a password protected dedicated computer network drive or a locked cabinet in the secured office of the 
Principal Investigator. The master list linking the study identifiers to the individuals and any PHI will be stored 
separately from the study data and kept in a password protected file on the MUSC secure network (MUSC 
patients) or VA network (VA patients).   
 
 
3.  POTENTIAL BENEFITS OF THE PROPOSED RESEARCH TO THE SUBJECTS AND OTHERS  
 
 
Subjects are hypothesized to benefit from the short intervention. Benefits could include more “normalized” 
reaching and muscle activity patterns in the arm most affected by stroke. However, because rehabilitation 
interventions are sometimes not effective, it is possible that there will be no long term benefits. The findings in this 
study may assist therapists in decision-making to optimize post-stroke rehabilitative therapy and enhance 
beneficial outcomes for persons with neurological injury and upper extremity impairment. The results of this study 
will be used to develop or refine rehabilitation treatments to promote more recovery of function. In addition, the 
study will provide critical information about how best to match a rehabilitation therapy to a patient given his/her 
specific upper extremity impairments. Our ultimate aim is to generate a scientific-based model for rehabilitation of 
post-stroke upper extremity motor impairment that is effective and efficient in accomplishing patient goals for arm 
and hand use. 
 
4.  IMPORTANCE OF THE KNOWLEDGE TO BE GAINED  
 
The present proposal seeks to systematically investigate the effects of an UE therapy strategy that is designed 
according to clinical and laboratory-based measurements of post-stroke UE motor function.  This Merit Review 
award, if funded, will enable a more comprehensive understanding of how to link the measurement of specific 

 
 
25 of  33 
motor processes that are impaired with injury to interventions targeted at these motor processes. It will also permit 
a greater understanding of how intervention affects specific motor processes. 
 
The risks to the subjects are minimal because the rehabilitation testing and programs are similar to those 
provided to persons with stroke in inpatient and outpatient rehabilitation settings.  The PI and study coordinator 
are both licensed occupational therapists with extensive experience providing rehabilitation programs to persons 
with stroke. There are no drugs, devices or biologicals in this study.  This study is comprised only of post-stroke 
rehabilitation aimed at improving arm movement through task-practice.  
 
 
5.  SUBJECT SAFETY AND MINIMIZING RISKS (Data and Safety Monitoring Plan) 
 
 Any adverse events will be recorded and monitored as required by our Institutional Review Board. On-campus 
medical services will be available in the event of adverse events to the subjects. Subjects will be able to terminate 
the movement analysis and/or task-practice protocol at their request at any time without prejudice. All documents 
with PHI (e.g., the ICF) will be stored in locked cabinets in the PI’s office in the MUSC College of Health 
Professions Research Building which is also a VA designated research space.  
 
All electronic files containing PHI will be stored on the VA network (VA patients) or MUSC network (MUSC 
patients) in password protected files which will be encrypted at the highest level of encryption available at the time 
of data storage. 
 
A licensed occupational or physical therapist will oversee all evaluation and treatment sessions. The therapist will 
monitor the participant for safety and offer rest breaks when he/she determines that the patient needs one. 
 
 
 
F. REFERENCES/LITERATURE CITATIONS______________________________________________________ 
 
1. 
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Kleim JA, Barbay S, Nudo RJ. Functional reorganization of the rat motor cortex following motor skill 
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Shumway-Cook A, Woollacott MH. Motor Control: Translating Research into Clinical Practice. 4th ed. 
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Dromerick AW, Lang CE, Birkenmeier RL, et al. Very Early Constraint-Induced Movement during Stroke 
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Lo AC, Guarino PD, Richards LG, et al. Robot-assisted therapy for long-term upper-limb impairment after 
stroke. N Engl J Med. May 13 2010;362(19):1772-1783. 
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Wolf SL, Winstein CJ, Miller JP, et al. Effect of constraint-induced movement therapy on upper extremity 
function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA. 2006;296(17):2095-2104. 
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Caimmi M, Carda S, Giovanzana C, et al. Using kinematic analysis to evaluate constraint-induced 
movement therapy in chronic stroke patients. Neurorehabil Neural Repair. Jan-Feb 2008;22(1):31-39. 
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Wu CY, Lin KC, Chen HC, Chen IH, Hong WH. Effects of modified constraint-induced movement therapy 
on movement kinematics and daily function in patients with stroke: a kinematic study of motor control 
mechanisms. Neurorehabil Neural Repair. Sep-Oct 2007;21(5):460-466. 
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Massie C, Malcolm MP, Greene D, Thaut M. The effects of constraint-induced therapy on kinematic 
outcomes and compensatory movement patterns: an exploratory study. Arch Phys Med Rehabil. Apr 
2009;90(4):571-579. 
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Woodbury ML, Howland DR, McGuirk TE, et al. Effects of trunk restraint combined with intensive task 
practice on poststroke upper extremity reach and function: a pilot study. Neurorehabil Neural Repair. Jan 
2009;23(1):78-91. 
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Alaverdashvili M, Foroud A, Lim DH, Whishaw IQ. "Learned baduse" limits recovery of skilled reaching for 
food after forelimb motor cortex stroke in rats: a new analysis of the effect of gestures on success. Behav 
Brain Res. Apr 9 2008;188(2):281-290. 
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Levin MF, Kleim JA, Wolf SL. What do motor "recovery" and "compensation" mean in patients following 
stroke? Neurorehabil Neural Repair. May 2009;23(4):313-319. 
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American Physical Therapy Association. Guide to Physical Therapist Practice. . Phys Ther. Jan 
2003;81(1):9-746. 
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American Occupational Therapy Association. Occupational Therapy Practice Framework: Domain and 
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Woodbury M, Velozo CA, Thompson PA, et al. Measurement Structure of the Wolf Motor Function Test: 
Implications for Motor Control Theory. Neurorehabil Neural Repair. Jul 8 2010. 

 
 
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Van Wijck FM, Pandyan AD, Johnson GR, Barnes MP. Assessing motor deficits in neurological 
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Fugl-Meyer AR, Jaasko L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient: a method 
for evaluation of physical performance. Scandanavian Journal of Rehabilitation Medicine. 1975;7(1):13-
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Duncan PW, Lai SM, Keighley J. Defining post-stroke recovery: implications for design and interpretation 
of drug trials. Neuropharmacology. Mar 3 2000;39(5):835-841. 
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Wright BD, Stone MH. Best test design. Chicago: Mesa Press; 1979. 
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Wright BD, Stone MH. Measurement Essentials. Wilmington, DE: Wide Range, Inc.; 1999. 
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Andrich D. A rating formulation for ordered response categories. Psychometrika. 1978;43:561–573. 
44. 
Woodbury ML, Velozo CA, Richards LG, Duncan PW, Studenski S, Lai SM. Dimensionality and construct 
validity of the Fugl-Meyer Assessment of the upper extremity. Archives of Physical Medicine & 
Rehabilitation. Jun 2007;88(6):715-723. 
45. 
Jette AM, Tao W, Norweg A, Haley S. Interpreting rehabilitation outcome measurements. J Rehabil Med. 
Oct 2007;39(8):585-590. 
46. 
Brunnstrom S. Motor testing procedures in hemiplegia: based on sequential recovery stages. Phys Ther. 
Apr 1966;46(4):357-375. 
47. 
Beer RF, Dewald JP, Rymer WZ. Deficits in the coordination of multijoint arm movements in patients with 
hemiparesis: evidence for disturbed control of limb dynamics. Exp Brain Res. Apr 2000;131(3):305-319. 
48. 
Lang CE, Beebe JA. Relating movement control at 9 upper extremity segments to loss of hand function in 
people with chronic hemiparesis. Neurorehabil Neural Repair. May-Jun 2007;21(3):279-291. 
49. 
Twitchell TE. The restoration of motor function following hemiplegia in man. Brain. 1951;74:443-480. 
50. 
Wolpert DM. Computational approaches to motor control. Trends in Cognitive Science. 1997(1):209–216. 
51. 
Newell KM, Liu YT, Mayer-Kress G. Time scales, difficulty/skill duality, and the dynamics of motor 
learning. Adv Exp Med Biol. 2009;629:457-476. 
52. 
Massie CL, Fritz S, Malcolm MP. Elbow extension predicts motor impairment and performance after 
stroke. Rehabilitation Research and Practice. 2011;2011:1-7. 
53. 
Ellis MD, Holubar BG, Acosta AM, Beer RF, Dewald JP. Modifiability of abnormal isometric elbow and 
shoulder joint torque coupling after stroke. Muscle Nerve. Aug 2005;32(2):170-178. 
54. 
Cirstea MC, Levin MF. Compensatory strategies for reaching in stroke. Brain. May 2000;123:940-953. 
55. 
Mirbagheri MM, Rymer WZ. Time-course of changes in arm impairment after stroke: variables predicting 
motor recovery over 12 months. Arch Phys Med Rehabil. Aug 2008;89(8):1507-1513. 
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Michaelsen SM, Dannenbaum R, Levin MF. Task-specific training with trunk restraint on arm recovery in 
stroke: randomized control trial. Stroke. Jan 2006;37(1):186-192. 
57. 
Wagner JM, Lang CE, Sahrmann SA, et al. Relationships between sensorimotor impairments and 
reaching deficits in acute hemiparesis. Neurorehabil Neural Repair. 2006;20(3):406-416. 
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Mirbagheri MM, Lilaonitkul T, Rymer WZ. Prediction of natural history of neuromuscular properties after 
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Mirbagheri MM, Rymer WZ. Predication of reflex recovery after stroke using quantitative assessments of 
motor impairment at 1 month. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:7252-7255. 
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Woodbury ML, Velozo CA, Richards LG, Duncan PW, Studenski S, Lai SM. Longitudinal stability of the 
Fugl-Meyer Assessment of the upper extremity. Archives of Physical Medicine & Rehabilitation. Aug 
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Velozo CA, Woodbury ML. Translating measurement findings into rehabilitation practice: An example 
using the Fugl-Meyer Assessment of the Upper Extremity with clients following stroke. Journal of 
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scale-derived computerized adaptive test. Phys Ther. Sep 2009;89(9):957-968. 
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Tao W, Haley SM, Coster WJ, Ni P, Jette AM. An exploratory analysis of functional staging using an item 
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Luft AR, Waller S, Forrester L, et al. Lesion location alters brain activation in chronically impaired stroke 
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Birkenmeier RL, Prager EM, Lang CE. Translating animal doses of task-specific training to people with 
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Beer RF, Ellis MD, Holubar BG, Dewald JP. Impact of gravity loading on post-stroke reaching and its 
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Ellis MD, Sukal-Moulton T, Dewald JP. Progressive shoulder abduction loading is a crucial element of 
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Davis JZ. Task selection and enriched environments: a functional upper extremity training program for 
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George MS BR. Transcranial Magnetic Stimulation in Clinical Psychiatry. American Psychiatric Publishing 
2007:l. 
 
 
G. CONSULTANTS__________________________________________________________________________ 
 
No Consultants 
 
 
H. FACILITIES AVAILABLE____________________________________________________________________ 
 
RESOURCES 
Scientific Environment 
 
The Ralph H. Johnson VA Medical Center and its partner academic affiliate, the Medical University of South 
Carolina (MUSC) offer a wealth of intellectual support and substantial institutional support for establishing a 
research program in neurorehabilitation with an emphasis in stroke rehabilitation, which is the goal of the PI. 
Together, the two institutions provide a superb scientific environment that will greatly increase the probability of 
success of the proposed study.  
 
The Ralph H. Johnson VA Medical Center and the MUSC are located in close proximity to one another on a 
shared campus with a majority of the staff having dual appointments (VA+MUSC). For example, the PI has an 
appointment as Assistant Professor in the Department of Health Sciences and Research in the MUSC College of 
Health Professions. There is a close, open working relationship between the local VA Medical Center’s PENTAD 
and ACOS for Research and counterparts at MUSC. This is especially evident within MUSC’s Strom Thurmond 
Biomedical Research Institute Building, half of which is leased by the VA to support VA ORD’s bench research 
and animal research activities. The distinction between MUSC and VA faculty is almost non-existent with 
investigators working side-by-side in an atmosphere that promotes intellectual sharing of scientific knowledge and 
expertise that has led to the development of new collaborations between VA and MUSC investigators.  This has 
allowed VA and MUSC investigators to propose and carryout a large number of innovative and intriguing 
investigations. Several of these collaborations have resulted in the discovery and use of new methodology not 
readily considered for use in a particular area of investigation that has added a whole new dimension to many of 
our investigators’ protocols. The VA Research Office provides excellent administrative support to investigators in 

 
 
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all areas. Of significant note is the level of support they provide in the preparation of applications in response to 
VA initiatives. They take the lead in coordinating and preparing all non-scientific aspects, including 
biosketches/other support forms, budgets and justifications, letters of support, intramural reviews, etc. which 
allows investigators to focus all their energies on the scientific aspects of the application. MUSC is a research 
intensive university, with an academic medical center, and is the state’s largest medical complex and the only 
tertiary/quaternary care referral center in the state. In FY 2009, MUSC faculty received grants and contracts 
totaling more than $217 million, with funding from NIH totaling $103.3 million. The College of Health Professions 
was ranked #9 in the country in total funding for similar colleges; the Department of Neurosciences, an integrated 
department of clinical and research neuroscientists that contains several nationally renowned senior investigators 
in stroke-research, ranks # 5 in the nation in NIH funding. MUSC is home to the JCAHO-certified SC 
Comprehensive Stroke and Cerebrovascular program, MUSC Stroke Center of Excellence and the REACH 
Stroke Network. The Stroke Center directed by Robert Adams, M.D. conducts innovative clinical trials throughout 
the state as well as through national networks, and offers remote urgent consultations through a new Web-based 
system that allows virtual examination of patients and CAT scans at community medical centers across the state.  
Center for Biomedical Imaging (CBI): The CBI provides state-of-the-art imaging resources to support clinical and 
research activities, provide opportunities to advance the imaging field, disseminate new technologies and 
approaches to the larger community, and train and mentor young investigators interested in developing and 
applying biomedical imaging to clinical and research problems. The CBI includes approximately 4500 square feet 
of space at 30 Bee Street, as well as approximately 9000 square feet in the new Bioengineering Building. This 
proposal will utilize the brain imaging and stimulation facilities available at the 30 Bee St. location of the CBI.  
The 30 Bee Street location is the main facility for human imaging research and houses a Siemens 3T TIM Trio 
MRI scanner equipped with integrated fMRI paradigm presentation equipment. It is located directly across the 
street from the main hospital and is 1 block from the Institute of Psychiatry.  The scanner operates with a 100% 
mandate for research use and is covered by a master research agreement with Siemens Medical. The site also 
contains an image analysis laboratory, a brain stimulation laboratory, and bioengineering facility along with 
subject interview and changing rooms. Research access is coordinated and billed through CBI and a web-based 
signup system. Researchers also have access to clinical Siemens 1.5T and 3T Verio MR scanners, located within 
the Radiology Department in the Clinical Sciences Building.  
 
Laboratory 
Upper Extremity Motor Function Laboratory: The Upper Extremity Motor Function Laboratory is a 900 square foot 
VA/MUSC laboratory located with the College of Health Professions Research Building (77 President Street, 
Room 207) on the campus of Medical University of South Carolina. This laboratory is designated as VA space 
through a formal Memorandum of Understanding between MUSC and the VA. The laboratory is located in the 
same building as the offices of the PI, Co-I, engineer and research therapy staff. It features equipment capable of 
collecting kinematic, kinetic, electromyographic, strength, and metabolic data. The motion analysis laboratory is 
adjacent to a small workshop available for the construction, repair, and alteration of simple mechanical devices. 
This space is located in close proximity to the VA Medical Center (within 2 blocks).  The laboratory is a shared 
resource of the college and is supported in part by the Department of Health Sciences and Research, of which the 
Co-PI is Chairman. The College enthusiastically supports the integration of VA research within its research 
portfolio. 
 
Clinical 
One avenue for recruitment of hemiparetic subjects for this project is the MUSC JCAHO-certified Stroke Center is 
directed by Robert Adams, M.D. The Stroke Center at MUSC includes highly trained neuroscience nurses, a 
neuroscience service line administrator, stroke neurologists, neurointensivists, interventional neuroradiologists, 
diagnostic neuroradiologists, cerebrovascular neurosurgeons, medical intensivists, neurosonology technologists, 
dedicated neurosciences critical care pharmacists, comprehensive rehabilitation services, dedicated case 
managers and social workers, and a hospital-based ground transport system. The 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 MUSC Stroke Center sees over 50 new stroke 
patients per month and routinely screens all patients for eligibility to research studies. Their database currently 
contains information on several hundred persons who have given consent to be contacted for stroke research 
studies. The Stroke Center research team will assist with recruitment by reviewing the patient rosters to identify 
potential participants. Potential participants will be given information while inpatient and again when they are seen 

 
 
30 of  33 
for follow up in the outpatient clinic. The Stroke Center research team will establish communication with the 
potential participants and act as a liaison with the PI to facilitate recruitment. In addition to facilitating subject 
recruitment, these facilities offer the PI opportunities to gain exposure to clinical problems by attending grand 
rounds, observing inpatient rehabilitation, and interacting with clinicians.  
In addition, investigators within the Department of Health Sciences and Research have established collaboration 
with Vanessa Hinson, M.D., Chief of Neurology at VAMC Charleston. In the last 5 year period, over 3500 veterans 
with stroke were seen throughout the Charleston Veterans Affairs catchment area along the South Carolina and 
Georgia coast. The Charleston VAMC conducts 4 neurology follow-up clinics per week in which Veterans with 
stroke are seen.  
 
 
Computer 
All staff have personal computers in their office that are linked together on a network. All office computers are 
equipped with necessary software for professional productivity (e.g., Microsoft Office, Internet Explorer, Adobe 
Acrobat, Matlab, etc.). The office computers are all on automated backup systems and linked for file sharing. 
Laboratory computers are also on the network, so that data are readily available to investigators. The PI has 
software available for conducting (a) item response theory data analyses (Winsteps Rasch Analysis, Rasch 
Unidimensional Modeling, Multilog Item Response Theory Modeling); (b) mathematical data analysis (Matlab) and 
(c) statistical data analysis (SPSS, SAS). 
 
Office 
Project investigators and staff have dedicated offices, telephones, and up-to-date office technology software. The 
PI and Co-I have offices in the College of Health Professions Research Building (with an approved VA off-site 
waiver). Project staff will have office space in the building. Conference telephones and videoconferencing 
capabilities are readily available. Well-appointed conference rooms with teleconferencing capabilities are readily 
available on a scheduled basis for conference calls and collaborator meetings. Support staff and standard office 
services are available to facilitate the project. 
 
 
I. INVESTIGATOR BROCHURE ____________________________________________________ 
No Investigator Brochure 
 
J. APPENDIX_______________________________________________________________________________ 
Patient-Targeted Upper Extremity Rehabilitation After Stroke – Recruitment Questionnaire 
 
 

 
 
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Patient-Targeted Upper Extremity Rehabilitation After Stroke – Recruitment Questionnaire 
Inclusion criteria: 
1. Experienced an ischemic stroke at least 3 months prior 
2. Passive range of motion in affected shoulder, elbow, and wrist within functional limits 
3. 20-80 years of age 
Exclusion criteria: 
1. Pain in the affected upper extremity that would interfere with movement 
2. Unable to understand 3-step directions 
3. Unable to attend the study-related treatment or evaluation sessions 
4. Orthopedic condition in back, UE, or impaired corrected vision that would alter kinematics of 
reaching. 
____________________________________________________________________________ 
1. Date of stroke________________________ 
 
2. Medical records and MRI or CT available for review  before participation yes 
no 
 
3. Adult age 20 – 80? 
 
Current age___________ 
 
 
4. Gender: 
 
 
Male 
Female 
 
5. Affected side:  
 
left  
right 
 
6. Do you have passive ROM 
 
a. Shoulder 
 
yes 
no 
Motions_________________________________________ 
Limitations_______________________________________ 
Pain with PROM 
yes 
no  
scale: 1  2  3  4  5  6  7  8  9  10 
Does your pain interfere with movement: 
yes 
no 
 
 
b. Elbow  
 
yes 
no 
 
Motions_________________________________________ 
 
Limitations_______________________________________ 
 
Pain with PROM 
yes 
no 
scale: 1  2  3  4  5  6  7  8  9  10 
Does your pain interfere with movement: 
yes 
no 
 
 
c. Wrist  
 
yes  
no 
Motions_________________________________________ 
Limitations_______________________________________ 
Pain with PROM 
yes 
no  
scale: 1  2  3  4  5  6  7  8  9  10 
Does your pain interfere with movement: 
yes 
no 
 
 
 

 
 
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7. Able to understand 3-step directions: 
 
 
 
 
yes 
no 
Ex:  
1. 
Place your right hand on the table.   
2. 
Tap your index (pointer) finger 3 times on the table.   
3. 
Make a fist with your right hand. 
 
8. Total study time will be 8 weeks.  All participants, in all groups will engage in 4 evaluations, 9 
rehabilitation sessions and 1 follow-up session which will be 30 days after the last rehabilitation 
therapy session.  The first session will take approximately 3-4 hours and all other sessions will 
take approximately 3 hours. 
Are you willing and available to participate in all sessions and follow-up 
yes 
no 
9. Do you have orthopedic back conditions that prevent you from: 
a. Sitting up for prolonged periods without trunk support 
 
yes 
no 
b. Sitting on a chair/stool without back support  
 
 
yes 
no 
 
c. Do you have pain during or after sitting unsupported on a chair 
yes 
no 
 
Pain  scale: 1  2  3  4  5  6  7  8  9  10 
Does your pain interfere with movement 
 
 
yes 
no 
 
d. Do you wear splints, slings, or other supportive devices  
on your hands or wrist 
 
 
 
 
 
yes 
no 
 
e. Do you wear an eye patch  
 
 
 
 
 
yes 
no 
 
f. Do you have impaired corrected vision that would alter your  
ability to reach or grasp objects? 
 
 
 
 
yes 
no 
 
 
Notes:___________________________________________________________________ 
 
________________________________________________________________________  
 
 
 
 
________________________________________________________________________  
________________________________________________________________________  
________________________________________________________________________  
________________________________________________________________________  
 
Questionnaire was conducted: 
Phone  
With Individual  
Caregiver 
Both 
 
 
 
 
 
In person 
With individual 
Caregiver 
Both 
 
______________________________ 
 
___________________ 
 
Recruiter  
 
 
 
 
Date of Questionnaire 
 

 
 
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