Assessment of muscle fatigue during biking.
The analysis of the surface myoelectric signal recorded while a muscle is performing a sustained contraction is a valuable tool for assessing the progression of localized fatigue. It is well known that the modifications of the spectral content of the myoelectric signal are mainly related to changes in the interstitial fluid pH, which, in turn, affect the membrane excitability of the active muscle fibers. This paper describes the effects of muscle fatigue on the surface myoelectric signal recorded from three thigh and leg muscles during biking, on a population consisting of 22 young healthy volunteers. The purpose of this study was to obtain normative data relative to an exercise protocol mild enough to be applicable, in the future, to pathological subjects as well. Each subject was asked to exercise 30 min on a cycloergometer at a constant velocity and against a constant torque. While subjects were biking, the surface myoelectric signal was recorded from the rectus femoris, the biceps femoris, and the gastrocnemius muscles. In this study, we considered two different aspects of muscle fatigue: first, the localized muscle fatigue as shown by the decrement of the instantaneous frequency of the myoelectric signal during the exercise; second, the modifications of the muscle ON-OFF timing, which could be explained as a strategy for increasing endurance by modifying the role of different muscles during the exercise. The first aspect was studied by obtaining the spectral characteristics of the signals by means of bilinear time-frequency transforms and by applying an original estimator of the instantaneous frequency of stochastic processes based on cross time-frequency transforms. Our results demonstrated that none of the subjects showed significant signs of localized muscle fatigue, since the decrement of the instantaneous frequency during the exercise was always lower than 5% of its initial value. Muscle ON-OFF timing was obtained by applying to the raw myoelectric signal a double threshold statistical detector to identify the time intervals during which the observed muscles were active. This demonstrated that the subjective feeling of fatigue each subject reported during the exercise did not cause a change of the activation strategy of the observed muscles. It is concluded that the experimental protocol herein described and the signal processing procedures adopted are appropriate for monitoring different effects of muscle fatigue during biking. Moreover, data obtained from our sample population can be considered as a reference for studying the manifestations of muscle fatigue in pathological subjects asked to follow a similar experimental protocol.
Knaflitz
Marco
M
Dipartimento di Elettronica, Politecnico di Torino, Turin 24-10129, Italy.
Molinari
Filippo
F
D000222:Adaptation, Physiological / Q000502:physiology; D000328:Adult; D000465:Algorithms; D000842:Ankle / Q000502:physiology; D001642:Bicycling / Q000502:physiology*; D004576:Electromyography / Q000379:methods*; D005080:Exercise Test; D005260:Female; D006801:Humans; D007717:Knee / Q000502:physiology; D008297:Male; D009119:Muscle Contraction / Q000502:physiology; D018763:Muscle Fatigue / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013223:Statistics as Topic