Modeling the Posture-Movement Continuum: Predictive Mapping of Spinopelvic Control Across Gait Speeds

Background: This study investigated how static postural parameters influence dynamic spinopelvic balance across varying walking speeds. One hundred healthy young adults (aged 18-25) underwent rasterstereographic assessment (DIERS 4Dmotion^®) to quantify static global alignment metrics including craniovertebral angle (CVA), Q-angle, sagittal and coronal imbalance, pelvic rotation, torsion, obliquity, vertebral rotation, thoracic kyphosis, lumbar lordosis, and pelvic tilt, followed by dynamic spinopelvic analysis during treadmill walking at 1, 2, 4, and 5 km/h. Methods: Multiple linear regression models were used to determine the predictive value of static postural measures for dynamic outcomes at each speed. At slower walking speeds (1-2 km/h), static alignment variables significantly predicted dynamic spinopelvic parameters (adjusted R² = 0.53-0.73; RMSE = 0.59-0.81), with CVA, sagittal imbalance, and pelvic torsion emerging as the most consistent predictors. Results: At higher speeds (4-5 km/h), predictive strength declined substantially (adjusted R² = 0.04-0.34), indicating a shift from posture-driven to neuromuscular-governed gait control. The Q-angle showed limited and inconsistent predictive value across all conditions. Conclusions: Overall, static postural alignment, particularly CVA, sagittal imbalance, and pelvic torsion, serves as a moderate predictor of spinopelvic dynamics at slow to moderate gait speeds but loses explanatory power as velocity increases, emphasizing the growing role of neuromuscular control in maintaining dynamic balance. These findings highlight the clinical relevance of integrating both static and dynamic assessments to comprehensively evaluate postural and locomotor function.