sEMG Based Movement Quantitative Estimation of Joins Using SVM Method
文献类型:会议论文
作者 | Liu, Dongsheng; Zhao XG(赵新刚)![]() ![]() ![]() |
出版日期 | 2014 |
会议名称 | 19th World Congress of the International Federation of Automatic Control |
会议日期 | August 24-29, 2014 |
会议地点 | Cape Town, South Africa |
关键词 | sEMG movement estimation quantitative estimation SVM method rehabilitation robot |
页码 | 12311-12316 |
通讯作者 | 赵新刚 |
中文摘要 | The sEMG based movement recognition developed rapidly in recent years, which focus on intention estimation that velocity and angle of movement joint are not concerned. This paper proposed a quantitative analysis method of sEMG, with ability to estimate motion of human joints, which can be used to control rehabilitation robot system control by patient’s own intention. The quantitative model of the relationship between sEMG signals and movement joint was established utilizing error Back Propagation artificial Neural Network and support vector machine with a Gaussian kernel, where the features of sEMG were taken as input. Considering of the actual demands of rehabilitation, the 1-DOF, 2-DOFs and 3-DOFs movement experiments were supposed to collect the information of joint angle and sEMG signals for model training. The result shows the angle prediction curve outputted by model of SVM has more than 90% consistency with the actual movement, while the model of BPNN gets a more imprecise output with complexity of movement arising. Initial online experiments on rehabilitation robot controlled by a healthy subject demonstrate that sEMG based movement control using the proposed method is feasible. |
收录类别 | EI ; CPCI(ISTP) |
产权排序 | 1 |
会议录 | The 19th World Congress of the International Federation of Automatic Control
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会议录出版者 | IFAC |
会议录出版地 | Zürich, Switzerland |
语种 | 英语 |
ISSN号 | 2405-8963 |
WOS记录号 | WOS:000391109500065 |
源URL | [http://ir.sia.cn/handle/173321/15406] ![]() |
专题 | 沈阳自动化研究所_机器人学研究室 |
推荐引用方式 GB/T 7714 | Liu, Dongsheng,Zhao XG,Ye D,et al. sEMG Based Movement Quantitative Estimation of Joins Using SVM Method[C]. 见:19th World Congress of the International Federation of Automatic Control. Cape Town, South Africa. August 24-29, 2014. |
入库方式: OAI收割
来源:沈阳自动化研究所
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