Muscle Synergies Estimation with PCA from Lower Limb sEMG at Different Stretch-Shortening Cycle

This study presents principal component analysis (PCA) intra-subject variability of lower limb surface electromyography (sEMG) at different muscle stretch-shortening cycle (SSC). Several key steps are presented on the research of muscle force production for human in-vivo and noninvasive studies as well as on SSC contribution at gait, run, and jump with the need for separation of muscle and tendon behavior. Complexity and unpredicted multiple muscle actuation are highlighted with the need for extraction of PCA components from muscle stretch-shortening cycle sEMG, namely on lower limb stereotyped muscle patterns assessed on standard maximum vertical jump (MVJ). The purpose of this study is to apply PCA to sEMG linear envelopes of lower limb selected muscles at different MVJ, to detect lower number of components explaining maximum sEMG variability, representative of low dimensional signal control on muscles synergies. Different MVJ were assessed with subject specific PCA of lower limb sEMG during Counter Movement Jump (CMJ), Drop Jump (DJ), and Squat Jump (SJ). Intra-subject variability of sEMG PCA allowed the detection of two components explaining maximum variability with different profiles and muscle grouping at CMJ, DJ, and SJ. First component (PC1), representing larger signal variability, presented higher value at SJ and DJ than CMJ, with the need for a higher number of PC’s to explain the same cumulative percentual variance at CMJ than DJ and SJ. Comparison with intra-subject linear (r) and cross-correlation (CCr) presented higher r and CCr at SJ and DJ than CMJ, with higher paired correlations at the muscles grouped on the same component. Comparison of intra-subject analysis with previous study on same subject single trial allowed subject-specific generalization of the preceding results.