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sEMG Based Movement Quantitative Estimation of Joins Using SVM Method
Liu, Dongsheng; Zhao XG(赵新刚); Ye D(叶丹); Zhao YW(赵忆文); Wu ZW(吴镇炜)
Department机器人学研究室
Conference Name19th World Congress of the International Federation of Automatic Control
Conference DateAugust 24-29, 2014
Conference PlaceCape Town, South Africa
Source PublicationThe 19th World Congress of the International Federation of Automatic Control
PublisherIFAC
Publication PlaceZürich, Switzerland
2014
Pages12311-12316
Indexed ByEI
EI Accession number20152200884862
Contribution Rank1
ISSN2405-8963
KeywordSemg Movement Estimation Quantitative Estimation Svm Method Rehabilitation Robot
AbstractThe 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.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/15406
Collection机器人学研究室
Corresponding AuthorZhao XG(赵新刚)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.College of Information Science and Engineering, Northeastern University, Shenyang, China
Recommended Citation
GB/T 7714
Liu, Dongsheng,Zhao XG,Ye D,et al. sEMG Based Movement Quantitative Estimation of Joins Using SVM Method[C]. Zürich, Switzerland:IFAC,2014:12311-12316.
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