Whole-Body Coordination and Spinopelvic Alignment During Yoga Standing Maneuvers: Comparing Practitioners With Non-Practitioners.

Understanding how humans coordinate multiple joints and body segments during complex whole-body tasks is essential for designing movement-based interventions. Yoga-inspired standing maneuvers, which combine upper-body alignment with lunging or stepping, provide a structured yet challenging experimental testbed. However, few studies have integrated spatiotemporal coordination and compensation strategies across different proficiency levels, limiting their adoption in rehabilitation and robotic applications. In this study, we analyzed whole-body kinematics during yoga standing maneuvers performed by practitioners and non-practitioners. Three-dimensional joint angle trajectories and spinopelvic alignment were quantified across movement initiation, posture holding, and return stages. Principal component analysis and continuous relative phase analysis were employed to characterize how redundancy is organized and coordinated. Practitioners exhibited smaller excursions in sagittal and rotational spinopelvic alignment and showed greater contributions from proximal trunk-pelvis coordination. This organization was adaptively modulated with increasing task demands through flexible inter-segment coordination. In contrast, non-practitioners exhibited greater involvement of distal joints, particularly ankle joints, and employed compensatory joint angle trajectories. Multivariate analysis further revealed that while lumbar motion strongly contributes to sagittal spinopelvic alignment in practitioners and non-practitioners, thoracic contributions differed, reflecting distinct patterns to achieve alignment. These findings demonstrate how task complexity and motor proficiency shape whole-body coordination and postural control during standing maneuvers. The quantitative coordination and alignment benchmarks identified here provide a basis for movement assessment and the development of rehabilitation and robotic assistance applications, with relevance for mitigating maladaptive compensation.