Earticle

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

저자

• Hsing-Chung Chen [ Department of Computer Science and Information Engineering Asia University Taichung 413305, Taiwan ] Corresponding Author
• Wei Lin [ Department of Computer Science and Information Engineering Asia University ]
• Pei-Yu Hsu [ Department of Computer Science and Information Engineering Asia University ] Corresponding Author

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