Authors
Rixi Huang, Guangjie Yu, Zhongxian Ma, Ying Zheng, Yue Zhang, Bingwei He, Xin-Yuan Chen
Published in
Journal of hand therapy : official journal of the American Society of Hand Therapists. Sep 30, 2026. Epub Sep 30, 2026.
Abstract
Traditional hand rehabilitation relies heavily on professional therapists, which brings great challenges and limitations to patients with hand dysfunction, making convenient and flexible home rehabilitation difficult to achieve.
This study aims to develop an innovative virtual hand rehabilitation system to improve patients' finger motor coordination and provide an effective, convenient home rehabilitation solution.
This study adopted a technical development and preliminary verification design. A targeted virtual rehabilitation system was developed and preliminarily validated through patient participation trials.
Based on the Unity platform and C# scripting, the system integrates VR technology, sEMG real-time signal monitoring and LSTM neural networks. Three virtual rehabilitation game scenarios were constructed to realize interactive training and accurate gesture recognition.
The system achieves over 90% accuracy in recognizing eight complex hand gestures. Ten patients with hand dysfunction participated in the test, and all feedback confirmed improved rehabilitation engagement, safety and convenience.
The proposed system has reliable recognition performance and good user experience. It offers a novel and feasible approach for home-based fine motor rehabilitation of hand dysfunction patients with broad application potential.
PMID:
42816195
Bibliographic data and abstract were imported from PubMed on 01 Oct 2026.
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