Synergistic recruitment of multi-scale myoelectric oscillations of upper limb during infant crawling

It has been widely accepted that the central nervous system (CNS) modulates muscle synergies to simplify motion control. However, it is still unclear that if there is a synergistic recruitment strategy to organize oscillation components of surface electromyography (sEMG) signals for limb movement. The sEMG signals were recorded from bilateral biceps brachii (BB) and triceps brachii (TB) muscles during infant crawling. The multivariate empirical mode decomposition (MEMD) was applied to decompose multi-channel sEMG signals into multi-scale oscillations. Then, non-negative matrix factorization (NMF) method was employed to extract oscillation synergy patterns. The results indicated that there were three stable oscillation synergies in sEMG signals for crawling movement, and the recruitment coefficient curves reflected the role of muscle during crawling movement. Our preliminary work suggested that synergistic recruitment of multi-scale oscillation components maybe a new way to understand the organization of MU recruitment strategy by the CNS.