Phase-Separated Complex Hilbert PCA on Markerless 3D Pose Estimation Data: A Global Phase Network and Its Extension to a Continuous Field on the Body Surface
Researchers have developed a novel method called Complex Hilbert Principal Component Analysis (CHPCA) to analyze whole-body coordination in sports motion using markerless 3D pose estimation data. This technique segments motion phases automatically and extends analysis to body surface mesh vertices, representing kinematic chains as continuous phase fields. The framework reveals a trunk-anchored global phase architecture and quantifies functional asymmetries between preparation and execution phases, bridging kinematic and kinetic descriptions of movement. AI
IMPACT Introduces a new analytical framework for biomechanics and sports science, potentially improving performance evaluation and injury prevention.