NRI:BMI Control of a Therapeutic Exoskeleton
Phase: NA
Conditions: Stroke, Hemiparesis
Sponsor: The University of Texas Health Science Center, Houston

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
NRI: BMI Control of a Therapeutic Exoskeleton 
 
NCT01948739 
 
Version Date: 11/11/2016 
 
 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
UNIVERSITY OF TEXAS – HOUSTON MEDICAL SCHOOL PROTOCOL 
 
1. PROTOCOL TITLE: NRI: BMI Control of a Therapeutic Exoskeleton (Brain Machine 
Interface Control of a Therapeutic Exoskeleton to Facilitate Personalized Robotic 
Rehabilitation of the Upper Limb) 
Protocol Nr: 
 
2. BACKGROUND and SIGNIFICANCE 
 
Relevance to robotic rehabilitation: Stroke is the leading cause of neurological disability in 
the United States [1] and accounts for the poor physical health and the social dysfunction 
evident in survivors [32]. Hemiparesis due to stroke is the primary cause of disability [33]. 
Arm paresis is perceived as the primary cause of disability by individuals who have suffered 
stroke because of the limitations it creates in performing activities of daily living (ADL) [34]. 
Rehabilitation of the impaired limb is essential for improving motor function after stroke [35- 
36], yet only 31% of stroke survivors receive outpatient rehabilitation (CDC 2007). Therefore, 
effective therapy for upper-limb paresis must be addressed. 
Approximately 80% of all stroke survivors suffer from upper limb paresis and only 18% of 
these individuals gain full motor recovery with conventional treatments in the year following 
stroke [2-4]. Thus, continued rehabilitation of the impaired limb is needed. Studies indicate 
that with proper treatment, upper extremity recovery can occur years after the stroke incident 
[34]. For example, repetitive, task specific training of the affected limb can result in significant 
motor recovery more than one year after the stroke incident [2]. Robotic devices are excellent 
candidates for delivering this repetitive and intensive practice. Experiments show that robot- 
assisted training of the impaired arm can be as effective as unassisted repeated practice of the 
impaired arm [37-38] and more effective than neuro-developmental therapy commonly used 
for motor recovery after stroke [39]. Furthermore, robotic rehabilitation systems offer 
increased efficiency, lower expenses, and new sensing capabilities to the therapist. 
Although various aspects of robotic rehabilitation have been investigated, a significant effort 
has been the design of novel rehabilitation robots, including the MIT-MANUS [5] and MIME 
[39-40], both of which were designed for rehabilitation of the proximal upper extremity joints. 
Due to the success of these early systems, robotic devices for the rehabilitation of distal joints 
of the upper limb have also been developed, such as the MAHI Exoskeleton [28-29], 
RiceWrist [26], the wrist module of the MIT-MANUS [41] and wrist rehabilitation devices 
developed by Hesse et al. [42] and Andreasen et al [43]. Most recently, rehabilitation robots 
with more degrees-of-freedom (DOF) such as Rupert [6], CADEN-7 [7] and ARMin [8] that 
are capable of actuating shoulder, elbow and wrist joints simultaneously have also been 
designed. 
From a mechanical design point of view, rehabilitation robots can be classified into two 
groups: end-effector based robots and exoskeletons. MIT- MANUS [5], a two degree-of- 
freedom (DOF) planar manipulator, is an example of end-effector robots. Based on an 
industrial 6 DOF PUMA robot, MIME [39-40] constitutes another example of end-effector 
based designs. Although end-effector based robots provide training capability encapsulating a 
large portion of the functional workspace, they do not possess the ability to apply torques to 
specific joints of the arm. Exoskeletons, on the other hand, are designed to resemble human 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
form and their structure enables individual actuation of joints. Examples of upper extremity 
rehabilitation exoskeletons include 5 DOF MAHI Exoskeleton [28-29], 5 DOF Rupert [6], 6 
DOF ARMin [8] and 7 DOF CADEN-7 [7]. Rehabilitation engineering research has 
increasingly focused on quantitative evaluation of residual motor abilities in an effort to obtain 
an objective evaluation of rehabilitation effects [30]. Exoskeletons offer the advantage of 
precisely recording and monitoring isolated joint movements of the arm and wrist, and hence 
make a better-suited design option versus end-effector based designs for this purpose. 
Neural Interfaces as tools to achieve human-machine confluence: The last decade has seen 
remarkable advances in algorithms for neural decoding and their use in assistive Brain- 
Machine Interface (BMI) systems to reconstitute motor function. Impressive feasibility 
demonstrations of non-human primates and humans controlling robotic limbs or computer 
cursors in real-time have been accomplished (Serruya et al. 2002; Taylor et al. 2002; Carmena 
et al. 2003; Wolpaw et al. 2004; Leuthardt et al. 2004; Hochberg et al. 2006, Velliste et al. 
2008; Ganguly and Carmena, 2009; Bradberry et al, 2011). Current BMI systems utilize 
neurophysiological or metabolic signals originating in the brain to control external devices or 
computers. These signals are fed into a decoding algorithm that transforms them into 
functional outputs to control robotic limbs or screen cursors (Carmena et al, 2003; Kim et al. 
2006; Hochberg et al, 2006). A closed control loop is normally established via the subject‟s 
visual feedback of the prosthetic device, although feedback from multiple modalities has been 
shown to enhance BMI control (Suminski et al, 2010). The neurophysiologic signals can be 
recorded from inside (invasive BMIs) or outside (non-invasive BMIs) the brain. Most BMIs 
are based on operant training of neuroelectric responses from single neuron spike trains (Fetz 
et al. 1969; Fetz, 2007) or scalp electroencephalogram (EEG) waves, event-related potentials 
and brain oscillations (for an overview see Birbaumer 2006b, Birbaumer & Cohen, 2007). 
Subjects or patients can learn to activate or deactivate external devices or computers based on 
voluntary modulation of their brain activity during motor imagery, however this training may 
take weeks to months and it is not clear whether these BCI systems are scalable to more than 3 
independent degrees-of-freedom (McFarland et al, 2010; Bradberry et al, 2011). Based on the 
more recent finding that BMI training can be used for selective induction of use-dependent 
CNS plasticity that might facilitate motor recovery, the concept of restorative BMI has 
emerged (Birbaumer & Cohen, 2007, Daly & Wolpaw, 2008, Broetz et al. 2010, Caria et al. 
2010, Dimyan & Cohen, 2011). Cortical control of neuroprosthetic systems is known to 
require adaptation in neural networks involved in motor planning and motor execution 
(Ganguly and Carmena, 2009; Velliste et al, 2008; Taylor et al, 2002). Although the long-term 
use of a BMI device has been shown to result in the formation of a stable, addressable and 
robust cortical map for 2D prosthetic control (Ganguly and Carmena, 2009), little is unknown 
about the nature of the cortical representation for BMI control of limb movements at the 
macro-scale of EEG. 
 
This research aims to accelerate the development, efficacy and use of robotic rehabilitation 
after stroke by capitalizing on the benefits of patient intent and real-time assessment and 
impairment. Validation will occur using the MAHI EXO-II exoskeleton robot in a clinical 
setting at The Institute for Rehabilitation and Research (TIRR) in Houston, Texas. Robotic 
rehabilitation is an effective platform for sensorimotor training in stroke patients. A robotic 
device enables accurate positioning of the impaired limb while simultaneously providing 
assistance and resistance forces and collection of motion data that can be used to characterize 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
the quality of the patient's movements. First, the MAHI EXO-II, a physical human-robot 
interface, will be augmented with a non-invasive brain-machine interface (BMI) to actively 
include the patient in the control loop, thereby making the therapy 'active' and engaging 
patients across a broad spectrum of impairment severity in the rehabilitation tasks. This 
approach capitalizes on the known benefits of patient intent in movement initiation observed in 
other clinical studies of robotic rehabilitation and in the beneficial effects of BMI use on 
cortical plasticity. Second, robotic measures of motor impairment, derived from real-time data 
acquired from sensors on the robotic exoskeleton and from the BMI, will drive patient-specific 
therapy sessions adapted to the capabilities of the individual, with the MAHI EXO-II 
providing assistance or challenging the participant as appropriate, in order to maximize 
rehabilitation outcomes. Assist-as-needed paradigms in robotic rehabilitation have been shown 
to be efficacious; however, such paradigms are passive and driven by performance metrics that 
have not been sufficiently validated and verified. Additionally, intense practice and continual 
'challenge' during therapy is known to improve rehabilitation outcomes. 
The key contributions of this work include: 
1) Adapting most advanced electroencephalogram (EEG) interface methods to stroke patients 
and developing a BMI for the control of the MAHI EXO-II that will a) increase upper limb 
function, b) advance understanding of brain plasticity, 
2) Determining appropriate robotic measures of motor impairment and associated control 
algorithms for patient-specific therapy; and 
3) Clinical validation in pilot studies to determine safety and efficacy of the proposed 
approach. 
The outcomes of this study will open new horizons for addressing both empirical problems, 
e.g. in the interpretation of measurement data from a variety of devices and subsequently in the 
formation of hypotheses regarding large scale brain function (interfacing the motor, perceptual 
and cognitive systems) and normative problems, e.g. building health innovations for restoring 
upper limb function after stroke. 
 
3. PURPOSE OF THE STUDY: 
The purpose of this study is to provide an alternative therapy modality where, the MAHI 
EXO-II, a physical human-robot interface, will be augmented with a non-invasive brain- 
machine interface (BMI) to actively include the patient in the control loop, thereby making the 
therapy 'active' and engaging patients across a broad spectrum of impairment severity in the 
rehabilitation tasks. Validation will occur using the MAHI EXO-II exoskeleton robot in a 
clinical setting at The Institute for Rehabilitation and Research (TIRR) Memorial Hermann in 
Houston, Texas. Robotic rehabilitation is an effective platform for sensorimotor training in 
persons suffering a cerebral vascular accident (stroke). A robotic device enables accurate 
positioning of the impaired limb while simultaneously providing assistance or resistance forces 
and collection of motion data that can be used to characterize the quality of the patient's 
movements. The aims are: 
Aim 1 (Year 1): To augment the MAHI EXO-II, a physical human-robot interface, with a 
non-invasive brain-machine interface (BMI) based on the EEG to actively include the patient 
in the control loop, thereby making the therapy 'active' and engaging patients in the 
rehabilitation tasks. This user-inspired approach capitalizes on the known benefits of patient 
intent in movement initiation observed in other clinical studies of robotic rehabilitation and in 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
the beneficial effects of BMI use on cortical plasticity. 
Aim 2 (Year 2): To develop robotic and electrophysiological (EEG-based) measures of motor 
impairment and recovery, derived from real-time data acquired from sensors on the robotic 
exoskeleton and from the BMI, that will drive patient-specific therapy sessions adapted to the 
capabilities of the individual, with the MAHI EXO-II providing assistance or challenging the 
participant as appropriate, in order to maximize rehabilitation outcomes. Assist-as-needed 
paradigms in robotic rehabilitation have been shown to be efficacious; however, such 
paradigms are passive and driven by performance metrics that have not been sufficiently 
validated and verified. Additionally, intense practice and continual 'challenge' during therapy 
is known to improve rehabilitation outcomes. 
Aim 3 (Years 3-4): To pursue longitudinal studies using the BMI-MAHI EXO in a cohort of 
patients with chronic and acute stroke to study the changes in cortical plasticity (using EEG 
and functional magnetic resonance imaging, fMRI), motor function, and human-machine 
confluence as the patients learn to control the robot exoskeleton, while improving their motor 
performance. 
 
 
4. DESCRIPTION OF STUDY: 
 
This study is designed to develop a therapy protocol that uses robotic activities and can be 
used in rehabilitation of upper-extremity function after stroke. 40 adult subjects who have 
developed hemiparesis after stroke will participate. In addition 10 health subjects will be 
recruited. 
 
First participants will go through a series of device try-out and mock therapy sessions (Aim2, 
year 1). We expect that each session will be two-hour-long and range from one to twelve 
sessions. The observation from these sessions will allow researchers to develop a therapy 
protocol to perform the treatment in a cohort of acute and chronic stroke subjects (Aim3, years 
2-4). 
 
Pre-screening Procedures: during the pre-screening process, potential subjects with stroke 
(acute or chronic) will be contacted by phone from a research personnel. The aim and details 
of the study will be explained in details and information such as demographics, medical 
history, medications being used, etc. will be gathered. Also subjects will be screened for MRI 
contraindications. The pre-screening will last about 30 minutes and will be performed in a 
private area. 
Once this information is collected, the researcher will consult with the Dr. Francisco (PI) and 
he will give final approval for the subject to come to TIRR Memorial Hermann for the 
screening procedure. 
 
Screening (duration: One hour): After subject arrives at TIRR a research personnel will 
meet him/her at the Motor Recovery Laboratory. The details of the study- specific procedures 
will be reviewed with the subject. Subject will be screened for inclusion and exclusion criteria. 
Signed and dated informed consent will be obtained. Demographics, medical history, and list 
of medications will be recorded. If the subject is female and of child-bearing age, a urine 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
pregnancy test will be requested before the subject undergoes MRI. A medication diary will 
be given to the subject and asked to document all changes in type and dosage of the 
medication he/she has been using throughout the study. This will allow us to differentiate a 
potential effect of a change in dosage or type of medication on movement recovery. After 
subject meets all Inclusion and Exclusion Criteria he/she will be enrolled into the study. 
 
Baseline Assessment (duration: two to three hours): The baseline assessment can be on the 
same visit as screening and will be performed in the Motor Recovery Laboratory. Subjects will 
be evaluated for cognitive, psychological, upper extremity motor and sensory functions and for 
their independence in daily living activities. Patients will also undergo one-hour MRI scan. 
 
The tests are: 
I- Baseline neurologic and functional status: 
In addition to abstracting basic demographic (e.g., age, sex, race/ethnicity) and clinical 
information (e.g., type and location of stroke) from the medical record, the following measures 
will be recorded before treatment by the evaluator: 
 
a) NIH Stroke Scale: The NIHSS is composed of 11 items, each of which scores a 
specific ability between a 0 and 4. A score of 0 indicates normal function, while higher 
score is indicative of some level of impairment. 
b) Manual Muscle Testing (MMT): The manual muscle testing will help to differentiate 
subjects with residual limb function. A score of 2 (-) in MMT, or the ability to move 
the limb segment with gravity eliminated, is required for elbow and wrist flexor and 
extensor muscle groups. 
c) Handedness: the dominance of right or left hand in daily activities will be measured 
with Edinburgh Handedness Inventory. Subjects will be questioned which hand they 
prefer to use for example to write, to draw to throw a ball, etc. (Oldfield R.C, 1971) 
d) Cognitive Functions: Folstein Mini Mental State Examination (MMSE) provides 
information about orientation, attention, learning, calculation, delayed recall, and 
construction. Several studies report acceptable validity of MMSE as a screening 
instrument and its relationship to functional outcome in stroke patients (Tombaugh et 
al. 1992; Agrell B, et al. 2000; Zwecker M, et al. 2002; Appelros et al,2005). 
e) Unilateral Spatial Neglect: Letter Cancellation Test is used to evaluate the presence 
and severity of visual scanning deficits, and is used to evaluate unilateral spatial 
neglect (USN) in the near extrapersonal space(Diller et al,1974) 
f) Sensory functions: The joint position sense of proprioception will be used to sense 
participant‟s ability to perceive the position of wrist joint, and be measured with vision 
occluded and minimal exteroceptive cues. Results will be documented as normal, 
impaired or absent (ref?). 
g) Psychological functions: Hamilton depression scale (HAM-D scale, Hamilton, 1960) 
will be used to determine patient‟s level of depression. The HAM-D form lists 21 
items, however the scoring is based on the first 17 items. Eight items are scored on a 5- 
point scale, ranging from 0=not present to 4=severe; nine are scored from 0-2. 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
II- Conventional Clinical Motor Tests 
 
The motor tests will be used to measure therapeutic improvement. The tests were selected to 
sample functional arm and hand movements, and have been shown to be sensitive to 
rehabilitation and demonstrated reliability. The tests will be administered by the outcome 
evaluator. The motor tests are: 
a) Fugl-Meyer Arm Motor Score: Is a stroke-specific, performance based impairment 
index. It quantitatively measures impairment, based on Twitchell and Brunnstrom‟s 
concept of sequential stages of motor return in hemiplegic stroke patients (Fugl-Meyer 
1975). It uses an ordinal scale for scoring of 32 items for the upper limb component of 
the F-M scale; (0;con not perform; 1:can perform partially; 2:can perform fully). 
Excellent interrater and intrarater reliability and construct validity have been 
demonstrated, and preliminary evidence suggests that the Fugl-Meyer assessment is 
responsive to change. 
b) Jebsen-Taylor Hand Function Test: (Jebsen et al., 1969): This motor performance test 
measures the time needed to perform 6 everyday activities (e.g., flipping cards, 
feeding) using both upper extremities. Administration of JTHFT subtests will be 
discontinued after 180 sec if the participant cannot complete the task by that time. The 
total JTHFT score is the sum of task completion times, with lower times representing 
better performance (Jebsen et al 1969). 
c) Action Research Arm Test: will be performed to assess subjects‟ ability to manipulate 
objects differing in size, weight and shape on a horizontal and vertical plane (Lyle, 
1981) 
d) Grip Strength: A dynamometer measures maximum gross grasp (kg) averaged over 
attempts with each hand. The minimum possible value of zero kg will be assigned 
when the participant cannot actively flex the fingers or grasp the dynamometer 
(Mathiowetz et al 1985). 
e) Pinch strength: A pinch gauge measures maximum pinch force (kg) averaged over 
attempts with each hand. The minimum possible value of zero kg will be assigned 
when the participant cannot actively squeeze the pinch meter between thumb and index 
finger. Pinch dynamo-metry appears to be useful to measure improvement in grip 
strength after hand-surgery in persons with tetraplegia (Vanden Berghe et al 1991). 
 
III- Robotic Surveys: 
a) Pain and Fatigue: will be measured on a visual analogue scale. After each training 
session, participants will be asked to rate their current pain and fatigue on an 11-point 
scale ranging from (0 = none to 10 = worst possible) (New et al 1997 ) 
b) Subject and Therapist Survey of Robotic Training: Subjects will be questioned after 
each session to rate their fatigue, discomfort, motivation, etc. level on a 4 point ordinal 
scale (0= strongly disagree, 4= strongly agree). Therapist will rate their perception on 
ease of set up, ease of use on a 4 point ordinal scale (0= strongly disagree, 4= strongly 
agree). 
c) System Usability Scale (SUS): Subjects will be questioned to understand their response 
to the BMI robotic training system by responding to questions on the SUS. 
 
IV- Robotic motor coordination measures: 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
Robotic measures will be calculated by post-processing the data acquired before, after 
and during treatment sessions. 
a) trajectory error (TE) measure: is defined as a normalized difference between the 
desired and the participant‟s trajectory from one point in the workspace to another. 
b) smoothness of movement (SM) measure: is a correlation coefficient that express the 
correlation between the participant‟s speed profile and a speed profile utilizing the 
minimum jerk principle. It takes values between 0-1, where 1 indicates perfect 
correlation with the optimally smooth speed profile and 0 indicating no correlation. 
Both TE and SM demonstrated strong correlation between clinical measures of arm 
function, such as Fugl-Meyer and Action research Arm test (Celik et al, 2010) 
 
 
V- 
Electrophysiological testing: 
Electroencephalogram (EEG): The EEG test is performed to measure the electrical 
activity in the brain and to examine the cortical dynamics. It also allows for better 
understanding of the effects of electrical activity generated in different areas of the brain. EEG 
only measures brain activity and does not induce electrical current in the brain. It is non 
invasive and has been used extensively in clinical practice for diagnosis or neurological 
conditions such as epilepsy. There are no risks associated with EEG other than a mild 
discomfort caused by the tightness of the net. The investigator will adjust the net to allow for 
the comfort of the subject. 
 
 
VI- 
Neuroimaging: MRI (structural & functional); 
The structural and functional MRI is performed to understand the reorganization of cortical 
areas associated with motor recovery. Morphological changes (structural plasticity) will be 
measured with structural MRI, and reorganization of neural activity (functional plasticity) will 
be measured with the functional MRI. MRI is noninvasive and has been used extensively in 
clinical studies. In order to eliminate the risks associated with magnetic field, subjects will be 
scanned for MRI safety. 
 
The clinical and behavioral tests will be administered by trained research personnel. 
 
Intervention Period (duration: two- hours per visit). The intervention part consists of two 
phases: 
a) Simulated therapy sessions 
b) Real therapy sessions 
 
a) Simulated therapy sessions (duration: two- hours per visit, up to twelve visits): 
First healthy and stroke affected subjects will be familiarized to control the InMotion Robot 
Manipuladum device with their thoughts. This calibration and familiarization with robotic 
training, may take over several sessions. During this period subjects will begin training to 
learn how to use their intentions to move the exoskeleton through repeated single joint and 
multi-joint movements while they wear the BMI system. During BMI training, healthy 
subjects/patients will essentially imagine moving their limb (muscle activity from the limbs 
will be monitored via electromyography, EMG, to ensure that only 'movement thoughts' are 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
used to control the robot) while watching the robot‟s 
resulting movement outputs (patients will be asked to 
actively attempt to perform the movements). 
Later, subjects will start using the exoskeleton device 
(Rice Wrist, MAHI Exo-II). During the training sessions 
the single joint and/or multi-joint targeted movements 
will be self-selected and self-initiated by the subject. The 
aim is to have them use the BMI and exploit the robot‟s 
capacity to increase the range of paretic arm movement 
by getting the robot to move up and down through a 
larger range than they can produce on their own (i.e., 
evoking robotic assistance). For each group this is 
accomplished by using the decoder‟s outputs to control 
the exoskeleton (Figure 2) by closing the loop via real 
time visual feedback of the robot‟s movement, that is, 
the reconstructed trajectories of the elbow and wrist 
joints decoded from EEG will be utilized to control the exoskeleton in real-time. The robot 
will operate in an “assist-as-needed” mode. Then after a rest period the subjects will sit 
passively while the robot replays the recorded movements, again with concurrent EEG 
recordings. 
 
We expect that each test session will be two-hour-long. These sessions will be repeated until 
subject gains confidence in using the robot arm. After a washout period of minimum 1-week 
from the last try-out session (if subject has participated in try-out sessions) subjects will 
participate in robotic training of arm movements 3 times/week for 4 weeks. Activities will be 
performed with the affected arm only. 
 
The tasks will be repeated multiple times per session for improved performance. Graphic 
feedback about performance will be given after each attempt in order to maintain motivation. 
Rest breaks will be given in order to avoid fatigue. At the end of each therapy session adverse 
events will be collected and the subject will be asked to rate his/her level of fatigue, pain, and 
satisfaction with the activities during the session. The staff member will record the time 
needed for equipment set-up, the ease of instructing the patient in the activity, and the potential 
therapeutic value of the activity. 
 
If possible data acquired before-and-after, and during the therapy sessions will be analyzed 
offline. If needed the existing protocol of 3x/week for 4 weeks will be modified and improved 
so that a final protocol is created and used in the second phase of the intervention period, i.e, 
active therapy sessions, in a cohort of subacute and chronic stroke subjects (Aim3, years 3-4). 
 
b) Real therapy sessions (duration: two- hours per visit, twelve visits). 
 
During this phase the therapy sessions will be supervised by a research personnel, who will set 
up the EMG, EEG, robotic device, instruct the subject and supervise the activity. During each 
session subject will be sitting on a comfortable chair and affected arm will be placed inside the 
padded exoskeleton the MAHI EXO-II. The real therapy sessions will be about two-hours long 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
and will be repeated three-times per week, over four-week training. 
The robotic training is investigational. The outcome measures of motor function have been 
used in clinical research but are also relevant to evaluate progress in clinical practice. 
 
Post-treatment and Follow-Up Assessment (duration: two to three hours): During this 
period subjects will be asked to come within a-week after they have completed the study, at 
week-2 and at month-2. Motor functions tests and robotic measures and MRI scan will be 
repeated. 
 
Videotape/ Photography: 
Portion of assessment sessions will be videotaped and/or photographed. Subjects will be asked 
to move or manipulate some objects with the arm while a project staff member will record or 
photograph. Subjects‟ consent will be required to perform and photography or videotaping. 
Screening, assessment and treatment sessions will be held at The Institute for Rehabilitation 
and Research and neuroimaging (MRI) will be performed at The Methodist Hospital or MRI 
imaging center at UTHealth Medical School. Calibration sessions will be held in part at University 
of Houston. Approximately 22 visits over a 6-months period will be required. Schedule of 
assessments is shown in Table 1. 
 
Table 1. Schedule of visits 
Assessment 
Screening 
Baseline 
Assessme 
nt 
Intervention period 
Post- 
treatment 
Assessment 
Follow-Up 
Assessment 
at 2weeks 
Follow-Up 
Assessment 
at 2 months 
Day7- to 
Day1 
Day 1 
Day 4(±3) to Day 15(±3) 
Day 19(±3) 
Day 33 (±3) 
Day 79 (±5) 
Visit 1 
Visit 2 
Visit 3-12 
Visit 15 
Visit 16 
Visit 17 
ICF 
X 
I/E Criteria 
X 
X 
Demographics 
X 
X 
Medical History 
X 
X 
NIH Stroke Scale 
X 
X 
X 
X 
Manual Muscle 
Testing (MMT) 
X 
Handedness 
X 
Mini Mental State 
Exam (MMSE) 
X 
Neglect- Letter 
Cancellation test 
X 
Proprioception- 
Joint sense 
X 
Depression 
X 
Fugl-Meyer 
X 
Ashworth Scale 
X 
X 
X 
X 
Grip Strength 
X 
X 
X 
X 
Pinch Strength 
X 
X 
X 
X 
JTHFT 
X 
X 
X 
X 
ARAT 
X 
X 
X 
X 
Robotic Measures 
X 
X 
X 
X 
Electroencephalogr 
aphy (EEG) 
X 
X 
X X X X X X X X X X 
X 
X 
MRI 
contraindications 
X 
MRI Scan structural 
X 
X 
MRI Scan 
X 
X 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
functional 
BMI controlled 
Robotic training 
X 
X X X X X X X X X 
Adverse Events 
X 
X 
X X X X X X X X X X 
X 
X 
Specimens to be collected, including frequency and size/amount: 
None. 
 
5. SUBJECT POPULATION: 
We assume to screen 60 adults with hemiparesis caused by stroke and enroll 30 of the screen 
participants over the course of the project from the TIRR Memorial Hermann outpatient clinic 
and from the Houston area. In order to reach the goal of „30 participants enrollment‟, we 
expect to screen 60 subjects with stroke. In addition 20 healthy subjects will be recruited in 
order to meet the goal of 10 healthy subjects‟ enrollment. 
Inclusion and Exclusion Criteria for Subjects with Stroke: 
 
Inclusion Criteria: 
Subject will be included if they have; 
1. Diagnosis of unilateral cortical and subcortical stroke confirmed by brain CT or MRI 
scan; 
2. Subacute or chronic stroke; interval of at least 3month and interval of at least 6 months 
from stroke to time of enrollment, respectively; 
3. No previous clinically defined stroke; 
4. Age between 18-75 years; 
5. Upper-extremity hemiparesis associated with stroke (manual muscle testing score of at 
least 2, but no more than 4/5 in the elbow and wrist flexors); 
6. No joint contracture or severe spasticity in the affected upper extremity: i.e., significant 
increase in muscle tone against passive ROM is no more than ½ of full range for given 
joint e.g., elbow, wrist and forearm movements. 
7. Sitting balance sufficient to participate with robotic activities; 
8. No neglect that would preclude participation in the therapy protocol; 
9. Upper limb proprioception present ( as tested by joint position sense of wrist); 
10. No history of neurolytic procedure to the affected limb in the past four months and no 
planned alteration in upper-extremity therapy or medication for muscle tone during the 
course of the study; 
11. No medical or surgical condition that will preclude participation in an occupational 
therapy program, that includes among others, strengthening, motor control and 
functional re-training of the upper limbs; 
12. No contraindication to MRI; 
13. No condition (e.g., severe arthritis, central pain) that would interfere with valid 
administration of the motor function tests; 
14. English-language comprehension and cognitive ability sufficient to give informed 
consent and to cooperate with the intervention. 
 
 
Exclusion Criteria: 
1. Orthopedic limitations of either upper extremity that would affect performance on the 
study; 
2. Untreated depression that may affect motivation to participate in the study; 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
3. Subjects who cannot provide self-transportation to the study location. 
 
 
Handling situation in case of a possible mood disorder: 
 
If subject‟s score in the depression scale suggest the possibility of a mood disorder, research 
team member will inform Dr.Francisco directly, so he can investigate it further and discuss 
options with the subject, including seeing a UTHealth psychiatrist, Dr.Dhamendra Kumar, 
who has a clinic at TIRR Memorial Hermann 2-3 times a week. Dr.Francisco will briefly 
document as a report in subject‟s research file. 
 
Inclusion and Exclusion Criteria for Health Subjects: 
 
Inclusion criteria: 
- able to understand and sign the consent form 
- age 18-65 
 
Exclusion criteria: 
- Previous history of or MRI findings consistent with brain tumors, strokes, trauma or arterial 
venous malformations 
- Contraindication to MRI 
- Pregnancy 
 
 
 
6. 
SUBJECT ENROLLMENT: 
Potential subjects will be identified by the following sources: 
1. Flyers will be posted in the TIRR Memorial Hermann outpatient clinic and TIRR 
Memorial Herman Adult and Pediatric Outpatient Rehabilitation. Attending physicians 
and therapists may refer their stroke outpatients to the study. 
2. Study will be advertised to general public through newspapers and radio programs. 
 
After subjects are identified by their treating physicians or therapists, they will be contacted by 
phone or e-mail. Alternatively they can contact study coordinator to request more information 
about the study. During a phone call, a brief pre-screening procedure will be applied. 
Demographics and medical information such as psychiatric, drug and alcohol history as 
inclusion and exclusion criteria will be gathered. Dr. Francisco will review the information 
gathered during phone screening and will agree or decline subject‟s enrollment into the study. 
Potential subjects will be invited to come for a screening visit to the UTHealth Motor 
Recovery Laboratory at TIRR Memorial Hermann. Any information gathered during phone 
screening will be stored in a locked file cabinet and password protected electronic file. 
 
During the screening visit, informed consent will be obtained by an investigator at TIRR. The 
subject will meet with the PI and the co-investigator. The test procedures will be described and 
the testing equipment will be shown to the subject. A co-investigator will clearly explain all 
the procedures and risks of the testing outlined in the consent form. The subject will be given 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
an hour to consider their decision and will be encouraged to ask questions, both during the 
initial interview and throughout the study. The PI or a co-investigator will answer any 
questions regarding the study at the time consent is given. Once enrolled, the subject may 
pause or terminate his/her participation at any time during the study. 
 
 
7. DATA ANALYSIS: 
Data analysis: Analyses will be performed with two-tailed significance tests at the 95% 
confidence level and are planned using parametric methods with continuous variables. 
Repeated measures ANOVAs with repeated measures on test-day (Day 1 to Day13) will be 
used to determine the effects for the EEG, robotic and clinical measures. This allows 
determination of the effects of BMI training on the given vraiables across test days. A 
Kenward Rogers adjusted degrees of freedom will be used due to the relatively small sample 
size. Power analysis from our preliminary studies (PI Boake, Co-I O‟Malley) indicates that, 
according to the improvements on FM, ARAT and JT measures, the current subject number 
will give us more than 90% of estimated power. We will compare clinical and robotic 
measures of motor impairment for each pair (FM-TE, FM-SM, ARAT-TE, ARAT-SM, JT-TE, 
and JT-SM) across all participants. We will use regression analyses to investigate the 
correlation between clinical, EEG and robotic measures at different days of treatment. The 
data are collected at the same stage of treatment for all participants to negate treatment effects. 
Regression analyses will be carried out using the 24 paired data sets, with the analysis 
providing the correlation coefficient r (Persons‟s r) and p value that represents the significance 
of the slope of the linear fit. A significant slope assures that the correlation coefficient r is also 
significant, i.e. there is a significant correlation between the variables. 
 
Analysis for neuroimaging scans: To assess structural changes, high-resolution anatomical 
images of the entire brain (using a 3 dimensional fast field echo sequence in axial orientation 
parallel to the line formed by the anterior and posterior commissures (AC, PC) will be 
acquired (in-plane resolution approx. 1 mm, slice thickness approx. 1mm, total acquisition 
time in the order of 10 min, parallel imaging options will be avoided to obtain high signal to 
noise ratios and good gray-white matter contrast). Images will be analyzed using the 
Freesurfer software (surfer.nmr.mgh.harvard.edu), which allows the segmentation and 
quantification of white/gray matter changes and the quantification of their volume. Changes in 
volumes of brain structures accessible to Freesurfer (cortical and subcortical structures) will be 
quantified during the course of the study. 
Diffusion tensor images (DTI), that is, spin-echo echo-planar images oriented in the same 
fashion as the anatomical images (parallel to the AC-PC line, in-plane resolution approx. 1.8 
mm, slice thickness approx. 3 mm, number of diffusion-weighted directions: approx. 25 with 
an estimated acquisition time in the order of 10 min) will be acquired to assess changes in the 
white matter fiber structure of the brain during the study. DTI images will be analyzed using 
the trackvis software (www.trackvis.org) by segmenting the pyramidal tracts and quantifying 
changes in fractional anisotropy (FA, a measure of tract integrity) during the course of the 
study. 
To assess motor function, fMRI image data will be acquired consisting of echo-planar images 
oriented in the same fashion as the high-resolution anatomical images (parallel to the AC - PC 
line). The fMRI paradigm will consist of visual and/or auditory stimuli activating the motor 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
cortex and will last about 10 - 15 min. Activation will be quantified by making use of the 
BOLD effect, thereby identifying and quantifying activation strength and extent of activated 
brain areas. AFNI (afni.nimh.nih.gov/afni) and FSL (www.fmrib.ox.ac.uk/fsl/) software 
packages will be used for the analysis. 
In addition to goal-directed fMRI images, also fMRI images will be acquired during which the 
subject is passively lying in the scanner with their eyes open (approx. 5min). These resting 
state images will be utilized to identify the extent of several networks in the brain, such as the 
motor network and the resting state network. Changes in the motor network may also be 
indicative of brain plasticity. Brain networks will be identified using the AFNI correlation 
analysis software. 
MRI is noninvasive and has been used extensively in clinical studies. In order to eliminate the 
risks associated with magnetic field, subjects will undergo the standard procedure for 
identifying potential contra-indications for MRI (at TMH, these consist of a standard 
questionnaire and a subsequent interview with a qualified MR expert). 
 
Cortical activity assessment with electroencephalogram (EEG): EEG activity will be assessed 
in all participants using standardized procedures during baseline assessment and at least a 
week before the first treatment session, and after the last treatment session. EEG will be 
sampled with 64 electrodes using an electrode cap, which places the electrodes in the standard 
10-20 international placement system (Electro-Cap International, Inc). Ground electrode is 
built into the cap and will be at site AFZ. 
 
Decoding of motor intent from scalp EEG - Neural decoders  can  be designed  to  predict 
state estimates as a discrete classification  of multiple  internal  states  such  as  intended 
spatial targets to move top or down or left or right (see Fig. 7 for an example of an 
experimental protocol involving center-out reaching movements to 3D spatial targets), or 
predictions of continuous time variables of  endpoint  hand  trajectories  or  angular 
kinematics that could serve as reference signals to  an upper  or  lower  limb  prosthetic 
device, powered exoskeleton or to control computer cursors, spelling devices or virtual 
keyboards. In this regard, we have demonstrated the feasibility of designing BEG-based 
neural interfaces to infer upper and lower limb movements from scalp EEG [34],[53-54]. 
Recently, we used a multivariate decoding  approach  grounded on  machine  learning 
methods that maximize the prediction accuracy of hand  kinematics  from  a  plurality  of 
scalp EEG electrodes. Cortical potentials and finger joint angles were  simultaneously 
recorded from five healthy human subjects while they naturally  reached  for  and  grasped 
any one of five objects (calculator, CD, espresso cup, zipper and a beer mug) in  front  of 
them.  Offline,  we  reconstructed  the  hand  kinematics  from  EEG  activity  and  compared 
it with the measured kinematics, with the decoding accuracy expressed as the correlation 
coefficient (r) between the two. To translate cortical activity into grasping kinematics, 
we extracted the fluctuations in the amplitude of slow  cmtical  potentials  filtered  in the  
low delta band (0.1-1.0 Hz) [34], and used a genetic algorithm  (GA)  to  optimize  the 
feature space of a linear Wiener filter decoder with respect to decoding accuracy (i.e., the 
fitness function for the GA). Next, we decoded the temporal evolution of synergies as 
subjects reached for and grasped the objects. Synergies were calculated as principal 
components (PCs) of the finger movement [78]. 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
Within subject comparison of after treatment vs. baseline will be performed, using paired t- 
test. Subjects‟ ratings of pain and fatigue after each therapy session will be compared the pain 
and fatigue ratings, to determine if there was unacceptable to subjects. The level of 
significance used will be p<0.05. 
 
8. POTENTIAL RISKS/DISCOMFORTS: 
Electroencephalography (EEG): 
The EEG test is performed to measure the electrical activity in the brain and to examine the 
dynamic changes. It also allows for better understanding of the effects of electrical activity 
generated in different areas of the brain. EEG only measures brain activity and does not induce 
electrical current in the brain. It is non-invasive and has been used extensively in clinical 
practice for diagnosis or neurological conditions such as epilepsy. There are no risks 
associated with EEG other than a mild discomfort caused by the tightness of the net or some 
discomfort and skin irritation. The investigator will adjust the net to allow for the comfort of 
the subject. 
 
Electromyography (EMG): The EMG, involves testing of the muscle activity thorough 
electrical signals. In the current project, it will allow to ensure that only „movement thoughts‟ 
(imagery movement) are used to control the robot. It is non-invasive and non-painful to the 
subject and has been used widely in clinical or research settings. The risks associated with 
surface EMG is some skin irritation. 
 
Magnetic Resonance Imaging (MRI): 
The structural MRI is performed to measure the structural connectivity of the corticospinal 
tract and the functional MRI is performed to measure signal changes in the cerebral cortex. 
MRI is noninvasive and has been used extensively in clinical studies. In order to eliminate the 
risks associated with magnetic field, subjects will be screened for MRI contraindication. All 
scanning sessions will be supervised by a research member. 
 
Robot-assisted training: 
Patients with spinal cord injury sometimes develop pain or discomfort in the shoulders and 
arm. In an ongoing study in our laboratory with subjects who are undergoing robotic training 
for three- hours per session and three-sessions per week for four weeks, didn‟t show any 
significant fatigue, discomfort or pain lasting longer than 24 hours after training (Yozbatiran et 
al, 2012). If there is evidence that pain or fatigue is worsened by the therapy, the sessions will 
be reduced or discontinued. All therapy sessions will be supervised by a project staff member. 
The robotic device has a safety shut-off mechanism that can be activated by the supervising 
staff member in order to immediately eliminate any mechanical force applied to the subject. 
 
Assessment/Questionnaires: 
All assessments will be performed in a designated room inside Motor Recovery Laboratory. 
None of these tests are either painful or uncomfortable to perform. In order to prevent potential 
embarrassment during the testing the test will be done individually and in private. 
If subjects feel uncomfortable in answering any of the questions they may stop the study at any 
time. 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
Monitoring plan for safety of subjects: 
In order to ensure subjects safety researchers will take following measures; 
1- Visits: All visits will be performed in an isolated room to protect participant‟s privacy. 
2- Training sessions: Dr.Yozbatiran is a physical therapist and a research member. She 
will be present during all training sessions and closely monitor subject for excessive 
fatigue, pain or discomfort. If any of these conditions occur, she will adjust the 
protocol to the functional level of subject by giving more frequent and longer rest 
breaks. If the problem persist for 24 hours at the same level of pain and/or fatigue or 
increases the symptoms will be reported as adverse event. 
3- Any adverse event, significant or non-significant will be reported to IRB by following 
IRB reporting guidelines. An adverse event log will be used. 
4- All personal information will be de-identified and saved in locked cabinets and 
password controlled computers and password controlled databases. 
 
 
 
9. POTENTIAL BENEFITS: 
 
As with any study focusing on basic research, the subjects will derive no direct benefit. 
The results of these studies may benefit subsequent future subjects if BMI control of a 
therapeutic exoskeleton proves to be effective. We envision that in the near future the 
information obtained from the proposed research will provide a better understanding for 
treatment options of upper extremity motor function in adults with stroke. 
The benefits of participating in this study may be improved arm and hand movement. 
However, there may be no benefit from participating in this study. 
 
10. 
RISK-BENEFIT RATIO: 
 
The clinical tests used in this study are widely used and are virtually risk free. There is some 
risk of fatigue, boredom or impatience, which will be counteracted by giving subjects 
sufficient breaks at specific time intervals and more breaks upon request. The robot devices are 
designed with hardware and software safety features that minimize the risk of injury due to the 
use of the robot. A series of automatic motion stop features are implemented to limit 
movement to a set of safe boundaries. The exoskeleton cannot move outside of the normal 
range of motion of the individual user. There is some risk of minor injury due to rubbing while 
using the robot. There is also a risk of pressure sores where the exoskeleton is attached to the 
user. A therapist will be present to apply padding to the robot where/when necessary to 
prevent rubbing. 
As with any research study, loss of confidentiality is a possible risk, although we will take 
every precaution to protect the subjects' privacy, including using identification codes on all 
forms, with only a single master key relating the identification codes to the subjects' 
identifying information, which will be kept in a locked cabinet at TMH, UT and UH. We will 
take every precaution to protect the subjects' privacy, including using identification codes on 
all forms, with only a single master key relating the identification codes to the subjects' 
identifying information, which will be kept in a locked cabinet. Scalp EEG is a non-invasive 
technique that does not present risks to the subject. The EEG procedures are widely used in 

IRB NUMBER: HSC-MS-13-0054 
IRB APPROVAL DATE: 11/11/2016 
 
research and are not known to be physically harmful to human subjects. There is a possibility 
that participants will become bored, tired or distressed during the experimental session due to 
the wearing of the EEG cap. Steps will be taken to avoid this and to address it promptly should 
it occur. Breaks will be taken if the participant becomes tired or distressed. Participants are 
free to call a break or end the experimental session whenever they see fit without penalty. 
Given the amount of information about brain dynamics and motor control to be learned from 
stroke patients, and the potential improvement of arm and hand movement in these patients, it 
is believed that these benefits outweigh the risks mentioned above. 
 
11. CONSENT PROCEDURES: 
 
Informed consent will be obtained from the subject at Motor Recovery Laboratory at The 
Institute for Rehabilitation and Research. After the patient is confirmed by Dr.Francisco (PI) 
as meeting study criteria and he/she is interested in participating, informed, written consent 
will be obtained by the study coordinator. 
In addition a photography/videotaping consent will be obtained from the subject, if he/she 
agrees to be photographed / videotaped during the assessments or treatment sessions. 
 
12. CONFIDENTIALITY PROCEDURE: 
 
All data will be coded with identification number. The database will be in a password – 
protected computer and kept in a locked file cabinet. 
 
13. COSTS 
 
The subject will not be expected to pay any costs. 
 
14. PAYMENTS: 
 
Subjects who travel to the study appointments will be reimbursed $20 per screening, 
assessment and treatment visit in order to pay for parking and travel. 
 
 
 
 
 
 
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