Turns-amplitude and power spectral analyses of surface EMG for assessing muscle fatigue and recovery during dynamic hand gripping

Abstract

Monitoring muscle fatigue and recovery is important during exercise. Alterations in the frequency structure of the myoelectric signals have been used to indicate muscle fatigue. The turns-amplitude analysis (TAA) reflects a muscle's summation and cancellation of action potentials. Its application in identifying fatigue and recovery under dynamic muscle contractions remains unexamined. This study investigated the ability of TAA and power spectral analysis of sEMG to identify fatigue and recovery under dynamic muscle contractions. TAA included the numbers of turns per second (T/s) and mean turn amplitude (MTA), while power spectral analysis included median frequency (MDF) as a parameter. Eighteen healthy adults performed a repetitive handgrip task until grip force failed below 50 % of MVC. The sEMG data and handgrip force were collected continuously during the fatigue and recovery. MDF, T/s, and MTA were calculated across four time points: pre-fatigue, post-fatigue, early-recovery, and late-recovery. Pearson correlations were used to examine associations between sEMG parameters and fatigue level. The study found that, compared with pre-fatigue, there was a significant decrease in the T/s and MDF during the post-fatigue state. As the muscle recovered, T/s and MDF returned to a similar level of the pre-fatigue states. Moreover, MDF and T/s showed a negative and moderate correlation with fatigue levels during the fatigue task. However, only T/s correlated with fatigue levels during the recovery task. These findings suggest that the T/s parameter could identify muscle fatigue during dynamic contraction and provide benefits in sports and rehabilitation science to establish optimal individual protocols.