RehabTouch: A Mixed-reality Gym for Rehabilitating the Hands, Arms, Trunk, and Legs After Stroke
Phase: NA
Conditions: Cerebral Stroke
Sponsor: Flint Rehabilitation Devices, LLC

 
 
 
 
Study Protocol and Statistical Analysis Plan 
 
for 
 
RehabTouch: A Mixed-Reality Gym for Rehabilitating the Hands, Arms, 
Trunk, and Legs after Stroke 
 
NCT03503617 
 
Document Date: 08/31/2021 
 
 

Trial Design  
This study was a single-site, single-blind randomized controlled trial comparing home-based 
therapy with RehabTouch to conventional therapy for individuals in the subacute phase of stroke. 
RehabTouch is a commercial home rehabilitation technology (sold as FitMi® by Flint Rehab) 
designed to put into practice clinically recommended design features for at-home rehabilitation 
technology. The study was performed at Rancho Los Amigos National Rehabilitation Center in 
Downey, CA. Participants were invited for an initial assessment to confirm they met the inclusion 
criteria and to establish baseline measures. Participants provided informed written consent. 
Qualifying participants were randomly assigned to either the RehabTouch group or the 
conventional group. Participants in both groups were instructed to perform self-guided therapy 
for at least three hours/week for three consecutive weeks. All participants received weekly 
phone calls from a supervising therapist. After the three-week exercise period, participants 
returned for an end-of-therapy assessment and to return study materials. Participants returned 
one month later for a follow-up assessment. The trial was pre-registered on ClinicalTrials.gov 
(NCT03503617) and approved by the Rancho Research Institute, Inc. Institutional Review Board 
at Rancho Los Amigos National Rehabilitation Center (IRB #263).  
 
Participants 
Inclusion criteria were: experienced one or more strokes between 2 weeks and 4 months prior; 
baseline UEFM Score >5 and ≤55 out of 66; absence of moderate to severe pain defined as a score 
of 4 or lower on the 10 point visual-analog pain scale; ability to understand the instructions to 
operate RehabTouch; and aged 18 to 85 years old, as older age could be a confounding variable. 
Exclusion criteria were: concurrent severe medical problems that precluded the individual from 
participating in routine rehabilitation; visual deficits defined as a score >1 on question 3 of the 
NIH Stroke Scale (NIHSS); severe cognitive deficits or apraxia defined as a score >0 on questions 
1a and 1c of the NIHSS; severe neglect defined as a score >1 on question 11 of the NIHSS; severe 
aphasia defined as a score >1 on question 9 of the NIHSS; and enrollment in other therapy studies. 
Recruitment aimed to balance the age, ethnicity, and gender of the study participants to be 
representative of Los Angeles County in California, USA. All participants provided informed 
consent.  
Using an estimated effect size of 1.05 based on long-term follow-up data from a previous arm 
training study during subacute stroke,[1] power analysis established that 21 participants in each 
group would provide a 90% chance of detecting a significant difference between RehabTouch 
and conventional therapy at the 0.05 significance level (two-tailed t-test). To account for 20% 
dropout, the target sample size was n = 25 participants in each group. 
Adaptive randomization was used to ensure matched levels of impairment between the 
RehabTouch and conventional therapy groups. Specifically, subjects were stratified by their 
UEFM Score into three levels (i.e. 5-22, 23-39, 40-55) and then randomized by alternating block 
allocation.[2] 

 
Intervention 
Participants randomized to the RehabTouch group were given a RehabTouch system with the 
custom 10” touchscreen tablet. They received 30 minutes of training on how to set up and use 
the RehabTouch system. They were instructed to spend most of their time performing upper 
extremity exercises, but access to the trunk and leg exercises in the RehabTouch software was 
not disabled.  
Participants randomized to the conventional therapy group were given a booklet of paper 
exercises that were selected from the same library of 40 exercises available in the RehabTouch 
software. 
For both groups, a supervising rehabilitation therapist selected the exercises for each participant 
based on their specific impairments. All participants received 30 minutes of training from the 
therapist on how to perform the selected exercises correctly.  
After the 3-week exercise period, participants returned for an end-of-therapy assessment. At this 
assessment, participants returned the RehabTouch system or the sensorized booklet of exercises 
for data collection. Participants returned one month later for a follow-up assessment. 
 
Outcomes 
The primary outcome measure was the change in Upper Extremity Fugl-Meyer (UEFM) score[3] 
from baseline assessment to one-month follow-up. UEFM was assessed at baseline, end-of-
therapy, and one-month follow-up. Secondary measures included the Box and Blocks Test,[4] the 
10 Meter Walk Test,[5] the Modified Ashworth Spasticity (MAS) scale[6] for the elbow, wrist, and 
fingers, and the Visual Analog Pain (VAP) scale for the upper extremity, all of which were assessed 
at baseline, end-of-therapy, and one-month follow-up. Motor Activity Log (MAL) was measured 
at end-of-therapy and one-month follow-up to assess self-reported quantity and quality of 
movement.[7] The European Quality of Life five dimensions, three levels (EQ-5D-3L) and its 
companion Visual Analog Scale (EQ-VAS) were measured at end-of-therapy and at one-month 
follow-up to assess overall perceived health state,[8], [9] and the Intrinsic Motivation Inventory 
(IMI)[10] categories of Interest/Enjoyment, Value/Usefulness, and Effort/Importance were 
measured at end-of-therapy to assess participants’ perceived motivation. These measures are 
widely used in stroke rehabilitation research and have good sensitivity and reliability. All 
assessments were performed by a blinded, trained evaluator. 
To assess adherence, the RehabTouch software recorded the date, time, and number of 
repetitions completed for each exercise, and the exercise booklet was placed in a sensorized 
folder that measured the times at which the participants opened the booklet.  

 
Statistical Methods 
Statistical analyses were performed using Matlab R2020 software. Change in UEFM score from 
baseline assessment to one-month follow-up was compared between the RehabTouch group and 
conventional therapy group using an unpaired two-tailed t-test. Three participants in the 
conventional therapy group did not perform their one-month follow-up assessment; one of these 
did perform the end-of-therapy assessment. For this one participant, the missing one-month 
follow-up data point was imputed for the primary outcome measure by adding the average 
change in UEFM score across all participants in the conventional therapy group from end-of-
therapy to one-month follow-up to this participant's end-of-therapy UEFM score. All other 
analyses were performed using only data from participants who completed all three 
assessments.  
MAS scores were grouped by flexion or extension items and summed to obtain lumped MAS 
extension and flexion values. We quantified items marked with a ‘+,’ with an additional 0.5 points 
for calculations. EQ-5D-L3 was analyzed following.[8], [9] IMI categories were compared across 
groups using Wilcoxon rank sum tests. For the secondary outcomes with baseline assessments, 
differences between groups at baseline and at one-month follow-up were assessed using 
unpaired, two-tailed t-tests. Within group changes from baseline to end-of-therapy and baseline 
to one-month follow-up were compared using paired, two-tailed t-tests. For the secondary 
outcomes without baseline assessments, end-of-therapy scores were compared to one-month 
follow-up scores using paired, two-tailed t-tests.  
To assess the ability of RehabTouch to motivate an appropriately high dose of home therapy, we 
performed a post-hoc exploratory analysis comparing the total number of repetitions that 
RehabTouch participants completed to a theoretical target dose of 2,700 repetitions. A dose of 
2,700 repetitions of UE exercise corresponds to 300 repetitions/hour (5 reps/minute) over 9 
hours of exercise, an intensity and duration sufficient to provoke a forelimb rehabilitative effect 
in a rodent model of stroke.[11] 
Certain participants were missing data at one or more time points for the secondary outcomes 
MAS, VAP and IMI. If a participant's record for a given measure was missing data, that participant 
was omitted from any analysis for that measure. Thus, for MAS calculations (RehabTouch n=13 
and conventional n=8), for VAP analysis (RehabTouch n=12 and conventional n=9), and for IMI 
analysis (RehabTouch n=13, and conventional n=11).    
 
Interim Analysis 
Due to the unexpected additional risks to participating in this study due to the COVID-19 
pandemic, an unplanned interim futility/efficacy analysis of the primary outcome measure was 
conducted after recruitment was halted in March 2020. Group labels were removed, and the 

analysis was reviewed by an independent investigator. For the futility analysis, a conditional 
power of 20% was selected. For the efficacy analysis, a P-value of 0.033 was selected using the 
Lan-DeMets alpha spending function for the Pocock boundary (n=27 out of a planned 50 at 
interim analysis).[12] 
 
References Cited 
[1] 
H. M. Feys et al., “Effect of a therapeutic intervention for the hemiplegic upper limb in the acute 
phase after stroke: a single-blind, randomized, controlled multicenter trial,” Stroke, vol. 29, no. 4, 
pp. 785–792, 1998. 
[2] 
D. Machin, “Clinical trials: Design, conduct, and analysis. Curtis L. Meinert (1986) Monographs in 
epidemiology and biostatistics. Volume 8. Oxford University Press. New York and Oxford. Pages 
469. £55 ISBN 5035682,” Hum. Psychopharmacol. Clin. Exp., vol. 3, no. 2, pp. 153–153, 1988. 
[3] 
J. See et al., “A standardized approach to the fugl-meyer assessment and its implications for 
clinical trials.,” Neurorehabil. Neural Repair, vol. 27, no. 8, pp. 732–41, Oct. 2013. 
[4] 
T. Platz, C. Pinkowski, F. van Wijck, I.-H. Kim, P. di Bella, and G. Johnson, “Reliability and validity 
of arm function assessment with standardized guidelines for the Fugl-Meyer Test, Action 
Research Arm Test and Box and Block Test: a multicentre study,” Clin. Rehabil., vol. 19, no. 4, pp. 
404–411, Jun. 2005. 
[5] 
F. M. Collen, D. T. Wade, and C. M. Bradshaw, “Mobility after stroke: reliability of measures of 
impairment and disability.,” Int. Disabil. Stud., vol. 12, no. 1, pp. 6–9. 
[6] 
R. W. Bohannon and M. B. Smith, “Interrater reliability of a modified Ashworth scale of muscle 
spasticity,” Phys Ther, pp. 206–207, 1987. 
[7] 
J. H. van der Lee, H. Beckerman, D. L. Knol, H. C. W. de Vet, and L. M. Bouter, “Clinimetric 
properties of the Motor Activity Log for the assessment of arm use in hemiparetic patients,” 
Stroke, vol. 35, no. 6, pp. 1404–1410, 2004. 
[8] 
“Calculating the U.S. Population-based EQ-5D Index Score | AHRQ Archive.” . 
[9] 
J. W. Shaw, J. A. Johnson, and S. J. Coons, “US valuation of the EQ-5D health states: development 
and testing of the D1 valuation model,” Med. Care, vol. 43, no. 3, pp. 203–220, Mar. 2005. 
[10] 
Intrinsic Motivation Inventory (IMI) – selfdeterminationtheory.org. . 
[11] 
R. L. Birkenmeier, E. M. Prager, and C. E. Lang, “Translating animal doses of task-specific training 
to people with chronic stroke in 1-hour therapy sessions: a proof-of-concept study.,” 
Neurorehabil. Neural Repair, vol. 24, no. 7, pp. 620–35, Sep. 2010. 
[12] 
D. L. DeMets and K. K. Lan, “Interim analysis: the alpha spending function approach,” Stat. Med., 
vol. 13, no. 13–14, pp. 1341-1352; discussion 1353-1356, Jul. 1994.