Estimation of Lower Limb Periodic Motions from sEMG Using Least Squares Support Vector Regression

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进机器人控制团队

	Estimation of Lower Limb Periodic Motions from sEMG Using Least Squares Support Vector Regression
	Li, Q. L.1; Song, Y.2; Hou, Z. G.3
刊名	NEURAL PROCESSING LETTERS
	2015-06-01
卷号	41 期号:3 页码:371-388
关键词	sEMG LS-SVR Motion estimation Neural network Support vector machine Rehabilitation
英文摘要	In this paper, a new technique for predicting human lower limb periodic motions from multi-channel surface ElectroMyoGram (sEMG) was proposed on the basis of least-squares support vector regression (LS-SVR). The sEMG signals were sampled from seven human lower limb muscles. Two channels sEMG were selected and mapped to muscle activation levels for angles estimation based on cross-correlation analysis. To deal with the time delay introduced by low-pass filtering of raw sEMG, a -order dynamic model was derived to represent the dynamic relationship between the joint angles and muscle activation levels. The dynamic model was built by data driven LS-SVR with radial basis function kernel. The inputs of the LS-SVR are muscle activation levels, and the outputs are joint angles of the hip and knee. In experiments, 48 sEMG-angle datasets sampled from six healthy people were utilized to verify the effectiveness of the proposed method. Result shows that the human lower limb joint angles can be well estimated in different motion conditions.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence
研究领域[WOS]	Computer Science
关键词[WOS]	NEURAL-NETWORK ; JOINT ; ELECTROMYOGRAPHY
收录类别	SCI
语种	英语
WOS记录号	WOS:000354203700006
公开日期	2015-09-22
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/8071]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队
作者单位	1.China Univ Min & Technol, Sch Mech Elect & Informat Engn, Beijing, Peoples R China 2.Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Li, Q. L.,Song, Y.,Hou, Z. G.. Estimation of Lower Limb Periodic Motions from sEMG Using Least Squares Support Vector Regression[J]. NEURAL PROCESSING LETTERS,2015,41(3):371-388.
APA	Li, Q. L.,Song, Y.,&Hou, Z. G..(2015).Estimation of Lower Limb Periodic Motions from sEMG Using Least Squares Support Vector Regression.NEURAL PROCESSING LETTERS,41(3),371-388.
MLA	Li, Q. L.,et al."Estimation of Lower Limb Periodic Motions from sEMG Using Least Squares Support Vector Regression".NEURAL PROCESSING LETTERS 41.3(2015):371-388.