A new method to estimate myoelectric manifestations of muscle fatigue

Mesin, Luca and Cescon, Corrado and Gazzoni, Marco and Merletti, Roberto and Rainoldi, Alberto (2008) A new method to estimate myoelectric manifestations of muscle fatigue. In: Proc. of the XVII Congress of the International Society of Electrophysiology and Kinesiology, 18-21 June 2008, Niagara Falls, Ontario, Canada.

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Myoelectric manifestations of fatigue are supposed to be mainly determined by two physiological factors: 1) the decrease of the conduction velocity (CV) of motor unit action potentials (MUAP) (peripheral fatigue), and 2) the increase of MU synchronization by the central nervous system (central fatigue). To describe separately the peripheral and central components of the myoelectric manifestations of fatigue, we investigated the following indexes: 1) mean spectral frequency – MNF, 2) median spectral frequency – MDF, 3) root mean square – RMS, 4) average rectified value – ARV, 5) estimation of muscle fiber conduction velocity – ECV, 6) percentage of determinism – %DET , 7) spectral indexes defined as the ratio between signal spectral moments – FIk, 8) MNF estimated by autoregressive analysis – MNFAR, 9) MNF estimated by Choi-Williams time-frequency representation – MNFCWD, 10) MNF estimated by continuous wavelet transform – MNFCWT, 11) signal entropy – S, 12) fractal dimension – FD. The indexes were tested with a set of synthetic EMG signals, with different CV distribution and level of MU synchronization. The indexes were calculated on epochs of 0.5 s. It was observed that ECV is uncorrelated with the level of simulated synchronization (promising index of peripheral fatigue). On the other hand FD was the index least affected by CV changes and most related to the level of synchronism (promising index of central fatigue). A representative application to some experimental signals from vastus medialis muscle during an isometric endurance test supported the results of the simulations. The vector (ECV, FD) is suggested to provide selective indications of peripheral and central fatigue. The description of EMG fatigue by a bi-dimensional vector opens new perspectives in the assessment of muscle properties, with potential application in both clinical and sport sciences.

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