Abstract
Surface electromyography (SEMG) has been used to detect the muscular activity in the field of biomechanics. By the way, the effects of muscular fatigue on SEMG have been studied and some frequency analysis methods such as first Fourier transform (FFT) and continuous wavelet transform (CWT) found the quantitative and qualitative alternation appear on the time-series of SMEG. However, it is difficult to estimate muscular fatigue quantitatively from SEMG analysis yet. Then, this study focuses on the pattern entropy method that compresses time-series signal with focusing on the instability, and attempts to apply this method to SEMG in order to quantitatively estimate the effect of muscular fatigue onto time-series signal of SEMG. The possibilities of the pattern entropy method to evaluate muscular fatigue from SEMG are discussed with comparing to the time-series data of power spectrum coefficient and frequency coefficient of the resut of gabor's CWT.
