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.