The Kinematic-Muscle Synergies during Infant Crawling: A Pilot Study

Many feature extraction algorithms have been separately used for kinematic or muscle synergy analysis during human movement. However, very few studies focus on the co-extraction of kinematic and muscle synergies. Therefore, the aim of this study was to propose a novel and efficient approach for extracting the kinematic-muscle synergies during infant crawling. Surface electromyography signals and three-dimensional joint trajectories were collected from 20 typically developing infants during self-paced hands-and-knees crawling. Angular accelerations of shoulder, elbow, hip and knee flexion/extension computing from those joint trajectories were divided into two independent directional positive degrees-of-freedom. The kinematic-muscle synergies and corresponding activation coefficients were extracted using the non-negative matrix factorization algorithm based on two selection criteria of synergy number (i.e., criterion 1: the total constraint, criterion 2: a combination of the total constraint and a local constraint for each joint/muscle). Then, the data of each joint/muscle were reconstructed by those synergies and corresponding activation coefficients. Our results indicated that the minimum number of kinematic-muscle synergies based on criterion 1 is less than that based on criterion 2. The data reconstruction of joint flexion/extension based on criterion 2 is better than that based on criterion 1, whereas the data reconstruction of muscles is similar between criterion 1 and 2. These promising results show the feasibility of applying the proposed approach to clinical assessments of motor function for infants.Clinical Relevance- Extracting kinematic-muscle synergies during infant crawling has the potential for professional therapists or rehabilitation physicians to conduct the early assessment and rehabilitation treatment of infants with the central nervous system disorders.