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Moustafa 1,2,3, Abdulla Alrahoomi 4, Mishal M. Aldaihan 5, Abdulrahman M. Alsubiheen 5, * and Iman Akef Khowailed 1,2, *  \nAcademic Editor: Darren Warburton  \nReceived: 10 November 2025  \nRevised: 1 December 2025  \nAccepted: 17 December 2025  \nPublished: 22 December 2025  \nCopyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.  \n1 Department of Physiotherapy, College of Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; [iabuamr@sharjah.ac.ae](iabuamr@sharjah.ac.ae) (I.M.M.)  \n2 Neuromusculoskeletal Rehabilitation Research Group, RIMHS–Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates  \n3 Faculty of Physical Therapy, Cairo University, Giza 12613, Egypt  \n4 Sheikh Tahnoon Medical City Rehabilitation Hospital, Al Ain, United Arab Emirates  \n5 Department of Rehabilitation Health Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box 10219, Riyadh 11433, Saudi Arabia; [mishaldaihan@ksu.edu.sa](mishaldaihan@ksu.edu.sa)  \n* Correspondence: [aalsubiheen@ksu.edu.sa](aalsubiheen@ksu.edu.sa) (A.M.A.); [ikhowailed@sharjah.ac.ae](ikhowailed@sharjah.ac.ae) (I.A.K.)  \nAbstract  \nBackground: This study investigated how static postural parameters influence dynamicspinopelvic 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.  \nKeywords: forward head posture; quadriceps angle; posture; gait; spinal balance  \n1. Introduction  \nThe static global alignment of the spine pelvis lower limb complex, encompassing sagittal imbalance (anterior–posterior trunk shift), coronal imbalance (lateral deviation in the frontal plane), pelvic rotation, pelvic torsion, pelvic obliquity, vertebral rotation, thoracic kyphosis, lumbar lordosis, pelvic tilt, craniovertebral angle (CVA), and Quadriceps angle (Q angle), plays a fundamental role in maintaining postural equilibrium and optimizing  \ndynamic movement [1–3] . Deviations in these alignment parameters alter the spatial relationship between body segments and can profoundly affect the mechanical function of the spine and pelvis during functional tasks s","cbCaioX8x3cFRJRX","https://ap.wps.com/l/cbCaioX8x3cFRJRX","pdf",2344720,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions\n# Introduction","[{\"question\":\"How were static and dynamic spinopelvic measures collected in this study?\",\"answer\":\"Static global alignment was quantified using rasterstereographic assessment (DIERS 4Dmotion®). Dynamic spinopelvic analysis was performed during treadmill walking at 1, 2, 4, and 5 km/h.\"},{\"question\":\"Which static alignment variables best predicted dynamic spinopelvic parameters at slower speeds?\",\"answer\":\"At slower walking speeds (1–2 km/h), craniovertebral angle (CVA), sagittal imbalance, and pelvic torsion emerged as the most consistent predictors.\"},{\"question\":\"Why did predictive strength decrease at higher walking speeds?\",\"answer\":\"At higher speeds (4–5 km/h), predictive strength dropped substantially, indicating a shift from posture-driven control toward neuromuscular-governed gait control.\"}]","Modeling the Posture-Movement Continuum - Predictive Mapping of Spinopelvic Control Across Gait Speeds | PDF",1790761907,48]