A bi-dimensional index for the selective assessment of myoelectric manifestations of peripheral and central muscle fatigue

Abstract

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.

Analysis of Vibration Exercise at Varying Frequencies by Different Fatigue Estimators

“…A recent study has suggested that the CV, MF, and RMS are more sensitive to peripheral fatigue [29]. Therefore, our CV, MF, and RMS results suggest VE, especially at 30 Hz, to produce a larger degree of peripheral fatigue as compared to control condition.…”

“…Therefore, the vibrationinduced fatiguing effect to the central nervous system should also be taken into consideration. In this study, the FD was estimated as an indicator for the central fatigue, as suggested by a recent study [29]. In ( [29]), the FD was found to decrease with increasing motor-unit synchronization, in silico, and during sustained contraction, in in − vivo [29].…”

“…Linear regression was then applied to the values obtained from all the epochs during each task and the slope of the regression line was used as the estimation for myoelectric muscle fatigue [47], [29]. Similar to previous studies [47], subject exclusion was performed based on the regression coefficient of MF and CV since they are reported to be much higher than that of RMS and FD [29], [47]. Subjects with MF or CV regression coefficient higher than 0.6 were included, resulting in 15 subjects for all the four fatigue indicators.…”

“…Recent studies indicated that the fractal dimension (FD) of the EMG signal decrease during fatiguing isometric contraction [29]. An estimate of the fatiguing effect of exercise can be derived as the angular coefficient of the linear fit of the MF, CV, RMS, and FD evolutions over time [26], [27], [29].…”

Typical Muscle Endurance Force Analysis of Upper Limb Pre and Post the Bed Test Using Detrended Fluctuation Analysis

“…Although many medical diagnosis methods can be use to survey the health state of the astronaut, however the size and the endurance time of the muscle force [2] can reflect the health state of a person directly. One of merits of the force analysis method consists that the muscle force can show us the integrated health state of people [3] such as the physiological health and the psychological health. Another virtue is that the muscle forces are very easy to measure.…”