Conformal, stretchable, breathable, wireless epidermal surface electromyography sensor system for hand gesture recognition and rehabilitation of stroke hand function

被引:1
作者
Yang, Kerong [1 ,2 ]
Zhang, Senhao [2 ,3 ]
Yang, Ying [4 ]
Liu, Xiaoman [4 ]
Li, Jiuqiang [1 ,2 ]
Bao, Benkun [1 ,2 ]
Liu, Chang [1 ,2 ]
Yang, Hongbo [1 ,2 ]
Guo, Kai [1 ,2 ]
Cheng, Huanyu
机构
[1] Univ Sci & Technol China, Sch Biomed Engn Suzhou, Div Life Sci & Med, Hefei 230022, Peoples R China
[2] Chinese Acad Sci, Suzhou Inst Biomed Engn & Technol, Suzhou 215011, Peoples R China
[3] Penn State Univ, Dept Engn Sci & Mech, University Pk, PA 16802 USA
[4] Peoples Hosp Suzhou New Dist, Dept Rehabil Med, Suzhou 215011, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金;
关键词
Epidermal sEMG sensor system; Hand gesture recognition; Rehabilitation of hand function; UPPER-LIMB; MECHANICAL MANIFESTATIONS; EMG; INTERFACES; CIRCUITS; THERAPY; FATIGUE; DESIGNS;
D O I
10.1016/j.matdes.2024.113029
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Surface electromyography (sEMG) plays a significant role in the everyday practice of clinic hand function rehabilitation. The materials and design of current typical clinic sEMG electrodes are rigid Ag/AgCl or flexible polyimide (PI) film, which cannot provide a stable interface between electrodes and skin for adequate long -term high-quality data. Thus, conformal, soft, breathable, wireless epidermal sEMG sensor systems have broad potential relevance to clinic rehabilitation settings. Herein, we demonstrate a stretchable epidermal sEMG sensor array system with optimized materials and structure strategies for hand gesture recognition and hand function rehabilitation. The optimized serpentine structures with marvelous stretchability and improved fill ratio, provide lower impedance and high-quality sEMG signals. Moreover, the easy-to-use airhole method further ensures stable and long -term contact with the skin for recording. In addition, integrated with a customized flexible wireless data acquisition system, the capability for real-time 8-channel sEMG monitoring is developed, and taking together with the CNN -based algorithm, the system can automatically and reliably realize the 7 kinds of hand gestures with an accuracy of 81.02%. Moreover, the low-cost yet high -performance epidermal sEMG sensor system demonstrated its conceptual feasibility in quantitatively evaluation of stroke patient 's hand and facilitating human -robot collaboration in hand rehabilitation by proof-of-the-concept clinical testing.
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页数:11
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