Identification of Model Parameters Basing on Matched Processing between Simulated and Recorded sEMG Signals / 航天医学与医学工程

ABSTRACT

Objective To identify the model parameters of surface Electromyography (sEMG) by comparison between simulated and recorded signals. Methods A physiological model of sEMG signal was established basing on several logical hypothetical conditions, such as motor unit action potentials (MUAP), motor unit recruitment and firing behavior caused by excitation, architecture of volume conductor and other simulated factors. According to the matched shapes between the simulated and recorded sEMG signals, a group of model parameters was obtained; according to the similar power spectrum variations of real sEMG signals, decreased muscle fiber conduction velocity (MFCV) was applied to simulate the sEMG signals of the fatigued muscle. Results The experimental results showed that the simulated superimposed MUAP shapes could be matched with the recorded MUAPs satisfactorily by adjusting some proper physiological parameters of the model. When the MFCV of each fiber was assumed to decrease, the mean and median frequency (MNF, MDF) of the simulated sEMG signals declined, and this phenomenon was very similar to that of the recorded sEMG signals and could be used to interpret the muscle fatigue process. Conclusion This model provides an effective approach to simulate real sEMG signals, and the simulated signals can also be used to help the analysis of recorded sEMG signals.