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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
DOI10.1109/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
专题光学影像学习与分析中心
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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