【摘要】 肌电信号的分解是根据肌电信号形成的机理 ,还原出构成它的各个运动单位动作电位序列 (MUAPT)的过程 .本文首先采用匹配滤波的方法 ,对组成EMG信号的各个运动单位动作电位 (MUAP)进行检测和提取 .算法能自适应地更新匹配滤波器和标准MUAP模板 ,以跟踪MUAP在发放过程中的缓慢变化 .利用获得的基本MUAP模板 ,根据叠加波形与构成它的各MUAP波形之间面积关系 ,得出可能的MUAP组合 .然后再根据每个MUAP的发放特点 ,采用模糊算法 ,从而得到最终的结果 .还利用模拟肌电信号和真实肌电信号对分解算法进行了实验 ,均取得了令人满意的效果更多还原

【Abstract】 Decomposition of the EMG signal is a procedure by which the EMG signal is separated into its constituent motor unit action potential trains(MUAPT). The EMG signal usually contains the superposition of the MUAP produced by a number of neurons in the vicinity of the electrode. It is therefore necessary to correctly classify the signals generated by different neurons. In this paper this problem is discussed and a classification scheme is developed. First, the basic motor unit action potentials (MUAPs) are obtained using matched filter, which enables waveform’s shape or amplitude during a muscle contraction. Then, based on these MUAPs, superimposed waveforms is classified according to area relationship and fuzzy membership function. The decomposition method has been tested on simulated and real EMG data, and the results are satisfactory.更多还原