The Influence of Lower Limb Muscle Selection on Synergy Analysis during Running - Yaru Chen; Wenqian Chen; Yongxuan Wang; Hailong Liu; Xiaohong Wang; Rong Liu (Computer Sciences & Mathematics Forum)
Muscle synergies have emerged as a novel framework that offers a deeper understanding of the physiological basis of motor control and have been extensively applied in various fields. This study aims to investigate muscle synergies, involving the selection of the muscles of the lower limb while running, including the deep muscles. The muscle synergies were identified from the 23 muscle activations generated by the OpenSim simulation and experimented EMG, respectively, and these outcomes were compared. Our results revealed an additional synergy required to achieve a comparable variability accounting for (VAF) levels when considering 23 muscles compared to 10 muscles. This study highlights that the potential contribution of deep muscles to explaining the muscle synergies involved in running. These findings provide valuable insights for a comprehensive understanding of muscle synergy during running and the neuromotor control of human locomotion. Further optimization of the experimental protocols and extraction methods is necessary to enhance the results of muscle synergy analyses and promote their broader application across various fields in the future.