Muscle fatigue and contraction intensity modulates the complexity of surface electromyography.

Nonlinear dynamical techniques offer a powerful approach for the investigation of physiological time series. Multiscale entropy analyses have shown that pathological and aging systems are less complex than healthy systems and this finding has been attributed to degraded physiological control processes. A similar phenomenon may arise during fatiguing muscle contractions where surface electromyography signals undergo temporal and spectral changes that arise from the impaired regulation of muscle force production. Here we examine the affect of fatigue and contraction intensity on the short and long-term complexity of biceps brachii surface electromyography. To investigate, we used an isometric muscle fatigue protocol (parsed into three windows) and three contraction intensities (% of maximal elbow joint moment: 40%, 70% and 100%). We found that fatigue reduced the short-term complexity of biceps brachii activity during the last third of the fatiguing contraction. We also found that the complexity of surface electromyography is dependent on contraction intensity. Our results show that multiscale entropy is sensitive to muscle fatigue and contraction intensity and we argue it is imperative that both factors be considered when evaluating the complexity of surface electromyography signals. Our data contribute to a converging body of evidence showing that multiscale entropy can quantify subtle information content in physiological time series.