Differential and directional body coupling analysis in Parkinsonian gait

Parkinson’s disease (PD) is a progressive neurodegenerative disorder primarily characterized by motor impairments and altered whole-body coordination. Objective and accessible approaches for quantifying inter-limb and cross-directional coupling during gait remain limited in clinical settings. Using a prospectively collected dataset of individuals with PD and healthy controls (HC), we propose a comprehensive analytical framework based on human pose estimation to extract time-series kinematic signals from key body landmarks. Coupling strengths between body segments were quantified to characterize whole-body coordination patterns. Statistical filtering identified discriminative body coupling factors that significantly differentiated PD from HC. The identified factors demonstrated clear and consistent alterations in coordination patterns across groups. Furthermore, multiple machine learning classifiers validated their discriminative capacity, achieving robust classification performance. Correlation analyses between the top 10 pre-specified directional body coupling factors and MDS-UPDRS III scores demonstrated modest but statistically significant associations in the full PD cohort ( n  = 121), with 8 of 10 factors surviving FDR correction (