Analysis of myoelectric signals recorded during dynamic contractions

This article presents the theoretical considerations that justify the choice of specific time-frequency transforms for processing nonstationary myoelectric signals as a method of studying fatigue prior to the failure point. It shows some preliminary results obtained by applying these techniques to computer-synthesized realizations of stochastic processes, as well as to real signals detected during different types of dynamic contractions of healthy human volunteers. Five different time-frequency transforms were applied in this study (the Wigner-Ville, the smoothed Wigner-Ville, the Cone kernel, the reduced interference, and the Choi-Williams), but for the sake of brevity, this article reports only the results obtained by applying the Choi-Williams transform, because the authors found it to be the most suitable for processing these specific signals.