Assessment of Muscle Fatigue from TF Distributions of SEMG Signals

Assessment of muscle fatigue involves the creation of indices based on the estimation of variables such as the instantaneous frequency IF and the instantaneous amplitude IA, which can be estimated from a time-frequency TF distribution of a surface electromyographic signal SEMG. Since during muscle fatigue there is a decrease of the IF and an increase of the IA, slopes from these parameters can be computed and used as indices to measure muscle fatigue. In this paper we present a comparison of four techniques used to build a TF distribution of SEMG signals, namely spectrogram, Wigner-Ville, Choi-Williams and smoothed pseudo Wigner-Ville. SEMG signals were recorded from thirty normal human subjects under specific physical routines to measure muscle fatigue, and TF distributions were computed for all the acquired signals. In order to confirm muscle fatigue, the computed indices were then correlated to the perceived discomfort levels reported by the subjects. Results show that although the spectrogram and smoothed pseudo Wigner-Ville have to overcome problems such as sizes of the time and frequency windows and cross terms, these two distributions provide equivalent slopes and valid indices of muscle fatigue for SEMG signals with low to medium nonstationarity.