Wavelet and short-time Fourier transform analysis of electromyography for detection of back muscle fatigue

Measurement of the time-varying characteristics of the frequency content of trunk muscle electromyography is a method to quantify the amount of fatigue endured by workers during industrial tasks, as well as a tool that may guide the training and rehabilitation of healthy and injured workers. Quantification of the change of signal power within specific frequency ranges may shed greater insight into the fatigue process. Sixteen healthy male subjects performed isometric trunk extension at 70% of their maximum voluntary contraction. Surface electromyography from medial and lateral erector spinae, and latissimus dorsi locations were processed using the short-time Fourier transform (STFT) and wavelet transform. Linear regression quantified the time rate of change of median frequency as well as frequency specific STFT filter and wavelet scale measures. The median frequency from the short-time Fourier transform declined by 22 Hz/min from an initial value of 77 Hz on average. The wavelet and STFT filter measures demonstrated this decline to be caused by a reduction in 209-349 Hz signal power in addition to an increase in 7-88 Hz signal power. A significant reduction in median frequency and significant elevation in 13-22 Hz wavelet signal component was detected in about 90% of the cases, indicating their use for detecting and quantifying fatigue