Identification of isotonic forearm motions using muscle synergies for brain injured patients | |
Geng, Yanjuan1; Ouyang, Yatao2; Samuel, Oluwarotimi Williams1; Yu, Wenlong1; Wei, Yue1; Bi, Sheng3; Lu, Xiaoqiang4; Li, Guanglin1 | |
2017-08-10 | |
会议名称 | 8th International IEEE EMBS Conference on Neural Engineering, NER 2017 |
会议录名称 | 8th International IEEE EMBS Conference on Neural Engineering, NER 2017 |
页码 | 633-636 |
会议日期 | 2017-05-25 |
会议地点 | Shanghai, China |
出版者 | IEEE Computer Society |
产权排序 | 4 |
摘要 | To effectively restore the fine motor functions of the forearm and hand of stroke survivors and patients with traumatic brain injury (TBI), recent studies have proposed an active rehabilitation concept based on the pattern recognition of electromyography (EMG) signals to decode the motor intent of the patients. The results from these studies suggested that pattern recognition of EMG signals associated with the limb motions could potentially aid the development of active rehabilitation robots. To obtain richer set of neural information from multiple-channel EMG recordings, this study proposed a muscle synergies based method for motor intent identification from high-density CP EMG signals recorded from eight TBI subjects. For baseline comparison, the linear discriminant analysis (LDA) based pattern recognition approach was also examined. The outcomes show that the proposed muscle synergy based method outperformed the commonly used LDA with more centralized distribution of motion classification accuracy across all the TBI subjects. And such an increment in accuracy suggests the feasibility CP of using muscle synergies for neural control in active rehabilitation for TBI patients. © 2017 IEEE. |
作者部门 | 光学影像学习与分析中心 |
DOI | 10.1109/NER.2017.8008431 |
收录类别 | EI |
ISBN号 | 9781538619162 |
语种 | 英语 |
ISSN号 | 19483546 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/29252 |
专题 | 光谱成像技术研究室 |
作者单位 | 1.CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), Guangdong; 518055, China 2.Guangdong Provincial Industrial Injury Rehabilitation Center, Guangzhou; 510440, China 3.National Research Center for Rehabilitation Technical Aids, Beijing; 100721, China 4.Xian Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xian; 710119, China |
推荐引用方式 GB/T 7714 | Geng, Yanjuan,Ouyang, Yatao,Samuel, Oluwarotimi Williams,et al. Identification of isotonic forearm motions using muscle synergies for brain injured patients[C]:IEEE Computer Society,2017:633-636. |
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