摘要
通过多通道信息检测与融合分析来探讨表面肌电(sEMG)信号分解问题,以获取准确的运动单位动作电位(MUAP)模式判别。采用结合连续小波变换和假设检验的波形检测方式从多通道sEMG信号中提取动作电位波形,在对动作电位波形空间分布特征信息融合分析的基础上通过层次聚类方法来确定MUAP类别数目,再利用模糊k均值算法以及针对未归类波形的波形剥离方法实现多通道sEMG信号的准确分解。实验结果表明,多通道sEMG信号中MUAP信息得到有效检测和模式分类。所采用方法利用多通道sEMG信号细致地获取了MUAP波形空间分布信息,能够取得满意的分解效果。
The decomposition method of surface electromyography （sEMG） signals was explored by using the multi channel information extraction and fusion analysis to acquire the motor unit action potential （MUAP） patterns. The action potential waveforms were detected with the combined method of continuous wavelet transform and hypothesis testing, and the effective detection analysis was judged with the multichannel firing processes of motor units. The cluster number of MUAPs was confirmed by the hierarchical clustering technique, and then the decomposition was implemented by the fuzzy kmeans clustering algorithms. The unclassified waveforms were processed by the template matching and peeloff methods. The experimental results showed that several kinds of MUAPs were precisely extrac ted from the multichannel sEMG signals. The space potential distribution information of motor units could be satis fyingly represented by the proposed decomposition method.
出处
《生物医学工程学杂志》
EI
CAS
CSCD
北大核心
2012年第5期948-953,共6页
Journal of Biomedical Engineering
基金
国家自然科学基金资助项目(30870656)
西南科技大学博士研究基金资助项目(08zx0110)
关键词
表面肌电信号
运动单位动作电位
多通道
分解
Surface electromyography （sEMG） Motor unit action potential （MUAP） Multi-channel Decomposi tion
