| 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
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| 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 |
| DOI | 10.1109/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 | 光谱成像技术研究室 |
| 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 |
| 推荐引用方式 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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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Real-time classifica（600KB） | 会议论文 | 限制开放 | CC BY-NC-SA | 请求全文 | ||
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