Developmental Postural Modeling: A Historical and Conceptual Narrative Review of Posture Assessment.

Background: Posture assessment has progressed from visual observation and descriptive classification to quantitative measurement, three-dimensional imaging, and artificial intelligence (AI)-assisted analyses. Despite these advances, uncertainty persists regarding normative interpretation, developmental significance, and prognosis, particularly during growth and maturation phases. Methods: This historical and conceptual narrative review synthesizes literature from PubMed/MEDLINE, Scopus, Web of Science, Google Scholar, and Semantic Scholar, with additional citation tracking and targeted searches of historical monographs and foundational sources. The final literature search was completed on 30 May 2026. The review was narrative rather than systematic, and no formal risk-of-bias or evidence-quality appraisal was performed. Reporting and methodological transparency were strengthened by referencing the SANRA principles for narrative reviews. Results: The literature supports several overlapping methodological traditions: observation and classification, quantitative measurement, three-dimensional reconstruction, and automated image- and data-based analysis. These approaches have accumulated rather than replaced one another. Across these traditions, a persistent measurement-interpretation gap remains: postural configuration can be characterized by increasing precision, whereas developmental reference trajectories and prognostic interpretations remain limited. Conclusions: Developmental Postural Modeling (DPM) is proposed as a hypothesis-generating conceptual framework for future research, initially emphasizing posture during childhood and adolescence, when growth and maturation are most explicit. The DPM is not a validated clinical tool and does not currently provide individual predictions or treatment recommendations. Its proposed role is to organize future longitudinal research integrating morphology, function, development, environment, time, advanced imaging, and computational analysis.