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Surface electromyography for noninvasive characterization of muscle. Exerc. Sport Sci. Rev., Vol. 29, No. 1, pp 20-25, 2001. Linear electrode arrays are used for noninvasive muscle characterization to study individual motor unit properties and the myoelectric manifestations of muscle fatigue during sustained contractions. The location of an electrode pair with respect to the innervation zone(s), the deterministic rather than stochastic nature of the signal, and the possibility of noninvasive fiber typing are discussed.

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The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply , even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Cover image:The cover image shows the generation, propagation and extinction of a motor unit action potential as detected on the surface of the skin by a two-dimensional electrode array placed above the biceps brachii muscle. The signal is spatially filtered with a longitudinal double differential filter, along the fiber direction. The interelectrode distance, in the row and column (fiber) direction, is 8 mm and the time interval between each instantaneous image and the next is 2 ms. The images are interpolated to obtain a smooth representation of the potential distributions (see also Fig. 4.5 on page 44).

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Two physiological factors are assumed in this paper to mainly determine the myoelectric manifestations of fatigue: (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 - FI(k), (8) MNF estimated by autoregressive analysis - MNF(AR), (9) MNF estimated by Choi-Williams time-frequency representation - MNF(CWD), (10) MNF estimated by continuous wavelet transform - MNF(CWT), (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 0.5s. 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 lateralis 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.