多通道表面肌电信号降噪与去混迭研究  

A Study of Multi-Channel sEMG De-Noising and Aliasing Removal

作　　者：席旭刚[1] 左静[1] 张启忠[1] 罗志增[1] 

机构地区：[1]杭州电子科技大学智能控制与机器人研究所,杭州310018

出　　处：《传感技术学报》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)

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.

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 

分 类 号：TP24[自动化与计算机技术—检测技术与自动化装置]