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Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors, Multiscale Permutation Entropy (MPE) is a suitable tool for capturing useful information from the ordinal patterns of sEMG time series. In a previous work, a theoretical comparison in terms of bias and variance of two MPE variants—namely, the refined composite MPE (rcMPE) and the refined composite downsampling (rcDPE), was addressed. In the current paper, we assess the superiority of rcDPE over MPE and rcMPE, when applied to real sEMG signals. Moreover, we demonstrate the capacity of rcDPE in quantifying fatigue levels by using sEMG data recorded during a fatiguing exercise. The processing of four consecutive temporal segments, during biceps brachii exercise maintained at 70% of maximal voluntary contraction until exhaustion, shows that the 10th-scale of rcDPE was capable of better differentiation of the fatigue segments. This scale actually brings the raw sEMG data, initially sampled at 10 kHz, to the specific 0–500 Hz sEMG spectral band of interest, which finally reveals the inner complexity of the data. This study promotes good practices in the use of MPE complexity measures on real data. [ABSTRACT FROM AUTHOR]

Abstract: During a sustained contraction, electromyographic signals (EMGs) undergo a spectral compression. This fatigue behaviour induces a shift of the mean and the median frequencies to lower frequencies. On the other hand, several studies conclude that the mean/median frequency can increase, decrease or remain constant with an increasing force level. Such inconsistency is embarrassing since the fatigue state may be influenced by the force level. In this paper, we propose a frequency indicator which is sensitive to the force level independently of the fatigue state evaluated at 70% of the maximal voluntary contraction. Ten healthy volunteers participated in the study and both surface EMGs (from the short head of the biceps brachii) and force signals were measured. This study compared force and fatigue effects on the EMGs during short (3-s) isometric contractions at different strength intensities and during a sustained isometric contraction until exhaustion. The EMGs partly show 1/f α spectral behaviours since their power spectral densities may experimentally fit with two linear segments in a log–log representation. The measured “right” slope produces variations of force as 20 times the variations of fatigue. 1/f α Behaviour may be related to stochastic fractals. This fractal indicator is a new frequency indicator that is thus complementary to other known classical frequency indicators when studying force during unknown fatigue states. [Copyright &y& Elsevier]

Abstract: The aim of the study was to confirm the hypothesis that the longer a contraction is sustained, the larger are the changes in the spatial distribution of muscle activity. For this purpose, surface electromyographic (EMG) signals were recorded with a 13×5 grid of electrodes from the upper trapezius muscle of 11 healthy male subjects during static contractions with shoulders 90° abducted until endurance. The entropy (degree of uniformity) and center of gravity of the EMG root mean square map were computed to assess spatial inhomogeneity in muscle activation and changes over time in EMG amplitude spatial distribution. At the endurance time, entropy decreased (mean±SD, percent change 2.0±1.6%; P <0.0001) and the center of gravity moved in the cranial direction (shift 11.2±6.1mm; P <0.0001) with respect to the beginning of the contraction. The shift in the center of gravity was positively correlated with endurance time (R 2 =0.46, P <0.05), thus subjects with larger shift in the activity map showed longer endurance time. The percent variation in average (over the grid) root mean square was positively correlated with the shift in the center of gravity (R 2 =0.51, P <0.05). Moreover, the shift in the center of gravity was negatively correlated to both initial and final (at the endurance) entropy (R 2 =0.54 and R 2 =0.56, respectively; P <0.01 in both cases), indicating that subjects with less uniform root mean square maps had larger shift of the center of gravity over time. The spatial changes in root mean square EMG were likely due to spatially-dependent changes in motor unit activation during the sustained contraction. It was concluded that the changes in spatial muscle activity distribution play a role in the ability to maintain a static contraction. [Copyright &y& Elsevier]