The 10th International Conference on Next Generation Computing 2024 (2024.11)바로가기
페이지
pp.169-172
저자
Hsing-Chung Chen, Wei Lin, Pei-Yu Hsu
언어
영어(ENG)
URL
https://www.earticle.net/Article/A468836
원문정보
초록
영어
This paper introduces a portable flexible wrist rehabilitation sensor system designed to support patients with hand function impairments from stroke or injury. The system collects flexible sensor data before and after rehabilitation to train a specialized AI model, utilizing a Long Short-Term Memory (LSTM) network for real-time analysis. This model evaluates wrist rehabilitation performance and degrees of freedom, using embedded sensors to classify and predict hand movements. Additionally, a user-friendly GUI allows patients to monitor their recovery progress. Compared to traditional rigid exoskeletons, this flexible sensor system offers a comfortable, natural hand simulation, reduces costs, and enhances rehabilitation customization and market viability.
목차
Abstract I. INTRODUCTION II. RELATED WORKS A. Design of Flexible Hand Exoskeleton B. Degrees of Freedom III. SYSTEM DESIGN IV. EXPERIMENTAL RESULTS AND DISCUSSIONS V. CONCLUSION AND FUTURE WORKS ACKNOWLEDGMENT REFERENCES