A Study on the Decomposition of Surface EMG Signals Based on Second Order Non-stationary Source Separation / 航天医学与医学工程

ABSTRACT

Objective To investigate the decomposition method of surface EMG(sEMG)signals based on Blind Source Separation and to detect the the motor unit action potential(MUAP)information.Methods Utilizing the sEMG signals recorded at low muscle contraction force(10% MVC),the methods of second order non-stationary source separation(SEONS)and FastICA were explored to analyze the sEMG signals decomposition.Results The experiment results showed that the MUAP information could be acquired by spike detection and pattern recognition after the decomposition of recorded sEMG signals using the proposed algorithm and FastICA method,but a little difference occurred due to the complexity of sEMG signals.Conclusion The non-stationary characteristic of sEMG signals is considered by the SEONS algorithm,and the proposed method can be applied in the sEMG signals decomposition.