Robotic Table and Serious Games for Integrative Rehabilitation in the Early Poststroke Phase: Two Case Reports.

BACKGROUND: BrightArm Compact is a new rehabilitation system for the upper extremities. It provides bimanual training with gradated gravity loading and mediates interactions with cognitively challenging serious games. OBJECTIVE: The aim of this study is to design and test a robotic rehabilitation table-based virtual rehabilitation system for functional impact of the integrative training in the early poststroke phase. METHODS: A new robotic rehabilitation table, controllers, and adaptive games were developed. The 2 participants underwent 12 experimental sessions in addition to the standard of care. Standardized measures of upper extremity function (primary outcome), depression, and cognition were administered before and after the intervention. Nonstandardized measures included game variables and subjective evaluations. RESULTS: The 2 case study participants attained high total arm repetitions per session (504 and 957) and achieved high grasp and finger-extension counts. Training intensity contributed to marked improvements in affected shoulder strength (225% and 100% increase), grasp strength (27% and 16% increase), and pinch strength (31% and 15% increase). The shoulder flexion range increased by 17% and 18% and elbow supination range by 75% and 58%. Improvements in motor function were at or above minimal clinically important difference for the Fugl-Meyer Assessment (11 and 10 points), Chedoke Arm and Hand Activity Inventory (11 and 14 points), and Upper Extremity Functional Index (19 and 23 points). Cognitive and emotive outcomes were mixed. Subjective rating by participants and training therapists were positive (average 4, SD 0.22, on a 5-point Likert scale). CONCLUSIONS: The design of the robotic rehabilitation table was tested on 2 participants in the early poststroke phase, and results are encouraging for upper extremity functional gains and technology acceptance. TRIAL REGISTRATION: ClinicalTrials.gov NCT04252170; https://clinicaltrials.gov/ct2/show/NCT04252170.

Novel integrative rehabilitation system for the upper extremity: Design and usability evaluation.

PURPOSE: Design and test the usability of a novel virtual rehabilitation system for bimanual training of gravity supported arms, pronation/supination, grasp strengthening, and finger extension. METHODS: A robotic rehabilitation table, therapeutic game controllers, and adaptive rehabilitation games were developed. The rehabilitation table lifted/lowered and tilted up/down to modulate gravity loading. Arms movement was measured simultaneously, allowing bilateral training. Therapeutic games adapted through a baseline process. Four healthy adults performed four usability evaluation sessions each, and provided feedback using the USE questionnaire and custom questions. Participant's game play performance was sampled and analyzed, and system modifications made between sessions. RESULTS: Participants played four sessions of about 50 minutes each, with training difficulty gradually increasing. Participants averaged a total of 6,300 arm repetitions, 2,200 grasp counts, and 2,100 finger extensions when adding counts for each upper extremity. USE questionnaire data averaged 5.1/7 rating, indicative of usefulness, ease of use, ease of learning, and satisfaction with the system. Subjective feedback on the custom evaluation form was 84% favorable. CONCLUSIONS: The novel system was well-accepted, induced high repetition counts, and the usability study helped optimize it and achieve satisfaction. Future studies include examining effectiveness of the novel system when training patients acute post-stroke.

Assistive game controller for artificial intelligence-enhanced telerehabilitation post-stroke.

Off-the-shelf gaming technology is designed for young, fit, and motor intact individuals. Artificial intelligence (AI) has a role in making controllers and therapeutic games adaptable to the disabled. Post-stroke rehabilitation outcomes can be enhanced by gaming technology within the home to enable engaging telerehabilitation. BrightBrainer™ Grasp (BBG) is a novel therapeutic game controller designed to adapt to arm and hand impairments post-stroke. It mediates intensive arm reach, grasp and finger extension training and has the ability to track relevant outcomes. The newly designed controller uses BrightBrainer gamification system with AI technology to provide automatic adaptation, requiring minimal clinician input. This article describes the BBG design, hardware, force and movement detection and calibration, and its integration with the therapeutic games. The use of AI in adapting a library of custom therapeutic games is also described. Results of a usability study with healthy individuals and related design modifications are presented, with implications for future trials.

Feasibility of integrative games and novel therapeutic game controller for telerehabilitation of individuals chronic post-stroke living in the community.

BACKGROUND: Intensive, adaptable and engaging telerehabilitation is needed to enhance recovery and maximize outcomes. Such services may be provided under early supported discharge, or later for chronic populations. A novel virtual reality game-based telerehabilitation system was designed for individuals post-stroke to enhance their bimanual upper extremity motor function, cognition, and wellbeing. OBJECTIVES: To evaluate the feasibility of novel therapeutic game controller and telerehabilitation system for home use. METHODS: Individuals chronic post-stroke and their caregivers were recruited (n = 8 + 8) for this feasibility study. One was a screen failure and seven completed 4 weeks (20 sessions) of home-based therapy with or without remote monitoring. Standardized clinical outcome measures were taken pre- and post-therapy. Game performance outcomes were sampled at every session, while participant and caregiver subjective evaluations were done weekly. RESULTS: There was a 96% rate of compliance to protocol, resulting in an average of 13,000 total arm repetitions/week/participant. Group analysis showed significant (p <.05) improvements in grasp strength (effect size [ES] = 0.15), depression (Beck Depression Inventory II, ES = 0.75), and cognition (Neuropsychological Assessment Battery for Executive Function, ES = 0.46). Among the 49 outcome variables, 36 variables (73.5%) improved significantly (p = .001, binomial sign test). Technology acceptance was very good with system rating by participants at 3.7/5 and by caregivers at 3.5/5. CONCLUSIONS: These findings indicate the feasibility and efficacy of the system in providing home-based telerehabilitation. The BrightBrainer system needs to be further evaluated in randomized control trials and with individuals early post-stroke.