摘要
通过数据采集装置同时采集多路表面肌电信号(sEMG)时,信号之间往往存在相互混迭的现象。为了得到有效的sEMG,提出了一种基于二代小波变换和独立分量分析(ICA)相结合的降噪与去混迭方法。先利用二代小波变换对sEMG降噪再利用改进的FastICA算法对降噪后的信号进行ICA分离,最后通过互相关系数验证去混迭效果。实验结果表明,所提方法能够有效降低噪声并去除相邻通道间产生的混迭。
There is an aliasing between the multi-channels of Surface Electromyographys（sEMG）when they are collected by a data acquisition device. The sEMG will inevitably be affected by noise due to the influence of acquisition equipment and the environment. In order to obtain unmixed sEMG,a new method is proposed. The method that combined by second generation wavelet transform and independent component analysis （ ICA ）：makes use of second generation wavelet transform to reduce noise in the sEMG,then,takes a ICA signal separation on sEMG by the improved FastICA algorithm. Finally,the paper introduces correlation coefficient to verify anti-aliasing effect. The experimental results indicate that this method is an effective way to de-noise and separate the mutual mixed sEMG.
出处
《传感技术学报》
CAS
CSCD
北大核心
2014年第3期293-298,共6页
Chinese Journal of Sensors and Actuators
基金
国家自然科学基金项目(60903084
61172134
61201300)
浙江省自然科学基金项目(LY13F030017
Y1111189)
关键词
表面肌电信号
独立分量分析
二代小波变换
FASTICA算法
互相关系数
surface electromyography （ sEMG ）
independent component analysis （ ICA ）
second generation wavelet transform
FastICA algorithm
cross-correlation coefficient
