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Real-time classification of forearm movements based on high density surface electromyography
Wei, Yue1,4; Geng, Yanjuan1; Yu, Wenlong1; Samuel, Oluwarotimi Williams1,2; Jiang, Naifu3; Zhou, Hui1; Guo, Xin4; Lu, Xiaoqiang5; Li, Guanglin1,2
2018-03-09
会议名称2017 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2017
会议录名称2017 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2017
卷号2017-July
页码246-251
会议日期2017-07-14
会议地点1-6-1 Nishizaki-cho, Okinawa, Japan
出版者Institute of Electrical and Electronics Engineers Inc.
产权排序5
摘要Partial or complete loss of the upper limb motor function has great impact on the activities of daily life (ADL) of post-stroke survivors. To improve the rehabilitation effect of fine motor function of forearms, a couple of recent studies focused on methods that try to decode the limb motion intent of patients through physical exercises. However, there exist a few studies on real-time active rehabilitation method for the classification of multiple hand movements. In the current investigate, a pattern-recognition based rehabilitation environment was set up using high-density surface electromyogram (HD-sEMG) and the real-time classification performance of 21 forearm motions was investigated with eight healthy subjects. The results showed that the average motion completion rate across all subjects was 91.17% + 2.86%, which suggests the potential of intention-initiated approach in assistive rehabilitation technique. © 2017 IEEE.
作者部门光学影像学习与分析中心
DOI10.1109/RCAR.2017.8311868
收录类别EI
ISBN号9781538620342
语种英语
EI入藏号20183105627013
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30545
专题光学影像学习与分析中心
通讯作者Geng, Yanjuan
作者单位1.Chinese Academy of Sciences (CAS), Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Shenzhen; 518055, China;
2.Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, Shenzhen; 518055, China;
3.Department of Orthopaedics and Traumatology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Pokfulam, Hong Kong;
4.Hebei University of Technology, Tianjin; 300130, China;
5.Xian Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xian; 710119, China
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Wei, Yue,Geng, Yanjuan,Yu, Wenlong,et al. Real-time classification of forearm movements based on high density surface electromyography[C]:Institute of Electrical and Electronics Engineers Inc.,2018:246-251.
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