A method of recognizing finger motion using wavelet transform of surface EMG signal

被引：46

作者：

Jiang, M. W. ^{[1
]}

Wang, R. C. ^{[1
]}

Wang, J. Z. ^{[1
]}

Jin, D. W. ^{[1
]}

机构：

[1] Tsinghua Univ, Div Intelligent & Biomech Syst, State Key Lab Tribol, Beijing 100084, Peoples R China

来源：

2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7 | 2005年

关键词：

wavelet transform; figure motion; artificial neural network;

D O I：

10.1109/IEMBS.2005.1617020

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper, an identification method of finger motions using the wavelet transform of multi-channel electromyography (EMG) signal is presented. The first step of this method is to analyze surface EMG signal detected from the subject's upper arm using the multi-resolution of wavelet transform, and extract features using the variance, maximum and mean absolute value of the wavelet coefficients. In this way, a new feature space is established by wavelet coefficients. The second step is to import the feature values into an Artificial Neural Network (ANN) to identify the finger motion. Based on the results of experiments, it is concluded that this method is effective in identification of finger motion. Thus, it provides an alternative approach to use the surface EMG in controlling the finger motion of a multi-fingered prosthetic hand.

引用

页码：2672 / 2674

页数：3

共 9 条

[1] Classification of the myoelectric signal using time-frequency based representations [J].