AI based sagittal spinal posture assessment for adolescent screening in low resource school settings

基于人工智能的矢状脊柱姿势评估在资源匮乏学校环境中用于青少年筛查

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Abstract

Adolescent spinal postural deviations are rising across Southeast Asia, driven by prolonged screen exposure and limited access to clinical screening in low-resource environments. To address this gap, we developed PostureGuard, a low-cost AI system that provides real-time posture assessment and school-based screening support. The system incorporates a Southeast Asia-calibrated pose estimation model, benchmarked against radiographic references and validated using wearable sensor measurements. In a field deployment involving 200 students across 15 Indonesian schools, PostureGuard achieved a mean absolute error below 2.3° for forward head angle estimation. We further identified a dose-response association in which each additional hour of daily screen time was associated with an estimated 2.1° increase in forward head angle. A preliminary six-month school implementation suggested improvements in posture-related indicators; however, these observations were not derived from a controlled clinical trial. PostureGuard has since been piloted within Indonesia's 2024 Digital Wellness Mandate initiative. This work presents a regionally calibrated AI-based posture screening framework with clinical benchmarking and demonstrated scalability for adolescent spinal health monitoring in resource-limited settings.

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