Speed-Dependent Multivariate Coordination Variability Using an Ellipse-Based Vector Coding Method

Vector coding is widely used to assess coordination and variability in movement control, yet its application is typically limited to bivariate analyses that focus on two segments or joints (e.g., knee-ankle coupling), despite human movement involving multiple interacting joints. Recent methodological advances have introduced an ellipse-based vector coding approach that enables coordination analysis in higher-dimensional spaces. Because gait speed systematically alters lower-limb kinematics, this study examined both bivariate and trivariate coordination variability of the lower extremity across the hip, knee, and ankle joints using an ellipse-based vector coding method, and compared these measures between slow and fast walking speeds. Mean between-cycle variability was computed to assess overall speed-related changes in coordination dynamics during the stance and swing phases. To determine when speed specifically affects coordination, statistical nonparametric mapping was applied across the entire gait cycle. Cross-correlation analyses compared variability patterns between bivariate and multivariate couplings. Results showed increased bivariate and trivariate coordination variability at faster walking speeds, with strong similarity in cross-correlation observed across knee-ankle, hip-ankle, and hip-knee-ankle couplings (from 0.82 to 0.96). These findings indicate the ankle's key role in driving variability and suggest that ankle-involving bivariate couplings capture the essential features of trivariate coordination during walking.