Muscle synergies and muscle networks in multiple frequency components in post-stroke patients

Abstract

As a neural control strategy employed by the central nervous system to control movements, the extraction of muscle synergies from a broad range of electromyographic signals has been the focus. Nevertheless, recent coherence analysis demonstrates distinct roles played in low-frequency components in motor control. This suggests that muscle synergies extracted from the low-frequency components can capture movement characteristics as done in the full-band. To investigate this issue, muscle synergies were extracted from three distinct frequency components (20–450 Hz, 20–30 Hz, 30–450 Hz) during spatial reaching movements in a group of healthy and stroke subjects. Synergy similarities were computed both within frequencies and between groups, and complex network analysis was conducted based on the group-averaged synergies. Results showed that the number and structure of muscle synergies, as well as network metrics, identified from the full-band (20–450 Hz) and low-frequency (20–30 Hz) exhibited high similarity between groups. These patterns diverged from those observed in high-frequency (30–450 Hz). The stroke did not induce significant alterations in muscle synergies. However, higher network metrics were identified in the full-band for one synergy. This study demonstrated the capacity of low-frequency components to perform muscle synergy analysis. These findings can help better understand the neural drive and motor control, potentially advancing the assessment of motor function and rehabilitation strategies.