Abstract: N. Babault, M. Hitier, C. Cometti (2022)

Simple Summary Neural alterations following the warm-up phase of a physical activity program are not clearly established with linear-based methods. However, it appears that nonlinear/complexity-based methods are sensitive enough to detect small and subtle changes in the individuals' neural drive. Accordingly, the present exploratory study aimed to apply different complexity-based methods to surface electromyography (EMG) of hamstring muscles to detect changes in neural activation after a standardized warm-up and after stretching exercises. Maximal and sub-maximal contractions were performed before and after these activities. The resultant EMG signal was processed using a linear analysis (the root mean square) and using nonlinear analyses: sample entropy, the recurrence quantification analysis and the detrended fluctuation analysis. These methods are well known to witness the presence of informationally rich variability. Our results revealed an increase in complexity of the EMG signal after warm-up and stretching during both maximal and sub-maximal contractions. In contrast, the linear analysis did not show any alteration. We concluded that, as for neuromuscular fatigue, complexity-based methods are sensitive enough to detect subtle changes in the EMG signal. The so-observed increase in complexity after warm-up and stretching would suggest that the neuromuscular system is in an optimized state for subsequent neuromuscular activity. This study aimed to apply different complexity-based methods to surface electromyography (EMG) in order to detect neuromuscular changes after realistic warm-up procedures that included stretching exercises. Sixteen volunteers conducted two experimental sessions. They were tested before, after a standardized warm-up, and after a stretching exercise (static or neuromuscular nerve gliding technique). Tests included measurements of the knee flexion torque and EMG of biceps femoris (BF) and semitendinosus (ST) muscles. EMG was analyzed using the root mean square (RMS), sample entropy (SampEn), percentage of recurrence and determinism following a recurrence quantification analysis (%Rec and %Det) and a scaling parameter from a detrended fluctuation analysis. Torque was significantly greater after warm-up as compared to baseline and after stretching. RMS was not affected by the experimental procedure. In contrast, SampEn was significantly greater after warm-up and stretching as compared to baseline values. %Rec was not modified but %Det for BF muscle was significantly greater after stretching as compared to baseline. The a scaling parameter was significantly lower after warm-up as compared to baseline for ST muscle. From the present results, complexity-based methods applied to the EMG give additional information than linear-based methods. They appeared sensitive to detect EMG complexity increases following warm-up.

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Usefulness of Surface Electromyography Complexity Analyses to Assess the Effects of Warm-Up and Stretching during Maximal and Sub-Maximal Hamstring Contractions: A Cross-Over, Randomized, Single-Blind Trial