Impacts of Motor Developmental Delay on the Inter-Joint Coordination Using Kinematic Synergies of Joint Angles During Infant Crawling.

Motor developmental delay (MDD) usually affects the inter-joint coordination for limb movement. However, the mechanism between the abnormal inter-joint coordination and MDD is still unclear, which poses a challenge for clinical diagnosis and motor rehabilitation of MDD in infant's early life. This study aimed to explore whether the joint activities of limbs during infant crawling are represented with kinematic synergies of joint angles, and evaluate the impacts of MDD on the inter-joint coordination using those synergies. 20 typically developing infants, 16 infants at risk of developmental delay, 11 infants at high risk of developmental delay and 13 infants with confirmed developmental delay were recruited for self-paced crawling on hands and knees. A motion capture system was employed to trace infants' limbs in space, and angles of shoulder, elbow, hip and knee over time were computed. Kinematic synergies were derived from joint angles using principal component analysis. Sample entropy and Spearman's rank correlation coefficients were calculated among those synergies to evaluate the crawling complexity and the symmetry of bilateral limbs, respectively. We found that the first two synergies with different contributions to the crawling movements sufficiently represented the joint angular profiles of limbs. MDD further delayed the development of motor function for lower limbs and mainly increased the crawling complexity of joint flexion/extension to some extent, but did not obviously change the symmetry of bilateral limbs. These results suggest that the time-varying kinematic synergy of joint angles is a potential index for objectively evaluating the abnormal inter-joint coordination affected by MDD.

Analysis of the Inter-Joints Synergistic Patterns of Limbs in Infant Crawling.

Hands and knees crawling is an important motor developmental milestone, which is characterized by diagonal coordination between upper and lower limbs. However, the features of inter-joint synergy within each limb in infant crawling is still not clear. Therefore, the aim of this study was to extract the inter-joint synergistic patterns during infant crawling and to test the possibilities of using the extracted inter-joint synergy to distinguish developmental delayed (DD) infants from typical developing (TD) infants. In this paper, kinematic data were collected from the shoulder, elbow, wrist, hip, knee, and ankle joints when 9 TD infants and 9 DD infants were crawling on hands and knees at their self-selected velocity. Tangential velocity was firstly calculated from the three-dimensional (3D) trajectory of each joint. Then, the non-negative matrix factorization (NMF) method was used to extract the joints synergistic patterns of each limb from the tangential velocity data. Our preliminary results showed that the crawling movement could be represented by a joint synergistic pattern, which consisted of three joints' data. In addition, we observed that the distal joint had a greater impact than the proximal joints during infant crawling. Moreover, it was found that the DD infants could be preliminarily distinguished from the TD infants by the features of inter-joint synergy during their crawling stage.

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.