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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
Conference Name2017 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2017
Source Publication2017 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2017
Volume2017-July
Pages246-251
Conference Date2017-07-14
Conference Place1-6-1 Nishizaki-cho, Okinawa, Japan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Contribution Rank5
AbstractPartial 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.
Department光学影像学习与分析中心
DOI10.1109/RCAR.2017.8311868
Indexed ByEI
ISBN9781538620342
Language英语
EI Accession Number20183105627013
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/30545
Collection光学影像学习与分析中心
Corresponding AuthorGeng, Yanjuan
Affiliation1.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
Recommended Citation
GB/T 7714
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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