重庆大学学报2017，Vol.40Issue(11)：83-90,8.DOI:10.11835/j.issn.1000-582X.2017.11.010
人体腿部表面肌电信号特征提取方法
Feature extraction method of sEMG of human legs
摘要
Abstract
Surface electromyography (sEMG) is one of the main information sources of human motion detection and has been widely used in the field of well-being of robots.We present a feature extraction method based on wavelet transform power for identifying the movement of human legs.The average power of the active segment in wavelet subspace is used to make up the feature vector according to the frequency domain distribution of the sEMG signal.In order to verify the effectiveness of the proposed method,we design and implement a small portable multi-channel sEMG signal acquisition system,and construct a classifier with support vector machine (SVM) to identify the leg movements.The results of the study show that the method can distinguish four kinds of common actions of the leg,the recognition rate of the same individual can reach more than 95％,and the recognition rate of different individuals can reach 85％,which can be applied to daily rehabilitation training of patients with lower limb movement disorders.关键词
sEMG信号/小波变换/平均功率/SVM/康复训练Key words
sEMG signal/wavelet transform/average power/SVM/rehabilitation training分类
信息技术与安全科学引用本文复制引用
王坤朋,庞杰,石磊,屈剑锋..人体腿部表面肌电信号特征提取方法[J].重庆大学学报,2017,40(11):83-90,8.基金项目
特殊环境机器人技术四川省重点实验室开放基金项目(15kftk03) （15kftk03）
西南科技大学校级创新基金资助项目(CX16-076) （CX16-076）
西南科技大学校内基金项目(14zx1107,14zx7124).Supported by Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan Province (15kftk03),Innovation Fund Project of Southwest University of Science and Technology (CX16-076) and Foundation of Southwest University of Science and Technology (14zx1107,14zx7124). （14zx1107,14zx7124）
