Research on upper limb motor function evaluation and rehabilitation training system of stroke patients based on artificial intelligence: A usability and feasibility study from therapist and patient perspectives.

Background and purpose: Upper limb dysfunction is a prevalent challenge post-stroke, necessitating innovative rehabilitation approaches. This pilot study evaluated the usability and feasibility of a novel multimodal virtual reality (VR) rehabilitation system that integrates an automated functional test for the hemiparetic upper extremity (FTHUE) assessment with personalized, task-oriented training in a clinical setting. Methods: The single-center, parallel-group pilot trial was conducted at the Rehabilitation Hospital of Fujian University of Traditional Chinese Medicine. Ninety-eight individuals were screened, from which 15 occupational therapists (mean clinical experience: 3.87 ± 4.84 years) and 15 stroke patients with mild upper limb impairment (Fugl-Meyer assessment score: 56.00 ± 5.25) were recruited. The intervention (a 1-hour hands-on VR session) was consistent across all participant groups, which incorporated neuroplasticity-based principles to deliver integrated sensorimotor training and multisensory feedback. Usability was evaluated using the system usability scale (SUS) and a custom-designed questionnaire. Results: All recruited participants completed the evaluation and were included in the analysis. Both groups exceeded the established usability threshold (SUS > 68). Therapists achieved a mean SUS score of 72.00 ± 6.69 (33% scoring ≥ 70) and patients scored 73.00 ± 7.69 (47% scoring ≥ 70). On the custom questionnaire (max 50), therapists scored 20.20 ± 2.74 and patients 19.20 ± 1.26. Therapists rated training enjoyment highest, exceptionally .superior to conventional therapy"u(4.47/5), while patients most valued ease of operation (4.20/5). No adverse events occurred during the trial. Conclusions: The VR system demonstrated good usability and was well-accepted by therapists and patients. Integrating automated assessment with personalized training shows promise as a complement to conventional rehabilitation. These findings, while promising, require confirmation in a larger definitive trial. Future work should optimize adaptive difficulty mechanisms and explore implementation in community and home settings. Trial registration: Chinese Clinical Trial Registration Center, ChiCTR2200060214. Registered May 22, 2022. https://www.chictr.org.cn/bin/project/edit?pid = 170137.