ICA-based muscle-tendon units localization and activation analysis during dynamic motion tasks

This study proposed an independent component analysis (ICA)-based framework for localization and activation level analysis of muscle-tendon units (MTUs) within skeletal muscles during dynamic motion. The gastrocnemius muscle and extensor digitorum communis were selected as target muscles. High-density electrode arrays were used to record surface electromyographic (sEMG) data of the targeted muscles during dynamic motion tasks. First, the ICA algorithm was used to decompose multi-channel sEMG data into a weight coefficient matrix and a source matrix. Then, the source signal matrix was analyzed to determine EMG sources and noise sources. The weight coefficient vectors corresponding to the EMG sources were mapped to target muscles to find the location of the MTUs. Meanwhile, the activation level changes in MTUs during dynamic motion tasks were analyzed based on the corresponding EMG source signals. Eight subjects were recruited for this study, and the experimental results verified the feasibility and practicality of the proposed ICA-based method for the MTUs' localization and activation level analysis during dynamic motion. This study provided a new, in-depth way to analyze the functional state of MTUs during dynamic tasks and laid a solid foundation for MTU-based accurate muscle force estimation, muscle fatigue prediction, neuromuscular control characteristic analysis, etc.