Comparison of Endurance Time Prediction of Biceps Brachii Using Logarithmic Parameters of a Surface Electromyogram during Low-Moderate Level Isotonic Contractions

At relatively low effort level tasks, surface electromyogram (sEMG) spectral parameters have demonstrated an inconsistent ability to monitor localized muscle fatigue and predict endurance capacity. The main purpose of this study was to assess the potential of the endurance time (T-end) prediction using logarithmic parameters compared to raw data. Ten healthy subjects performed five sets of voluntary isotonic contractions until their exhaustion at 20% of their maximum voluntary contraction (MVC) level. We extracted five sEMG spectral parameters namely the power in the low frequency band (LFB), the mean power frequency (MPF), the high-to-low ratio between two frequency bands (H/L-FB), the Dimitrov spectral index (DSI), and the high-to-low ratio between two spectral moments (H/L-SM), and then converted them to logarithms. Changes in these ten parameters were monitored using area ratio and linear regressive slope as statistical predictors and estimating from onset at every 10% of T-end. Significant correlations (r > 0.5) were found between log(T-end) and the linear regressive slopes in the logarithmic H/L-SM at every 10% of T-end. In conclusion, logarithmic parameters can be used to describe changes in the fatigue content of sEMG and can be employed as a better predictor of T-end in comparison to the raw parameters.

Automated summary

The study assessed the potential of predicting endurance time using logarithmic parameters compared to raw data. Significant correlations were found between log(T-end) and the linear regressive slopes in the logarithmic H/L-SM, suggesting that logarithmic parameters can be used as a better predictor of T-end.