AI-Based Imaging Screening System for Bone Development in Rural Children: An Intervention Framework Integrating the Health Belief Model
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Abstract
Inadequate health education and limited parental awareness remain major barriers to the early screening and long-term management of postural skeletal disorders among rural children. With the rapid development of electromagnetic imaging, mobile sensing, and intelligent communication technologies, AI-assisted visual screening has become an effective approach for improving accessible healthcare services in resource-constrained environments. Guided by the Health Belief Model (HBM), this study systematically analyzes existing imaging-based posture screening products and identifies deficiencies in behavioral guidance and continuous intervention support. Questionnaire findings indicate that rural caregivers generally accept mobile imaging screening but encounter practical obstacles, including limited time, transportation inconvenience, and insufficient follow-up participation. Based on comparative product analysis and user surveys, a stage-oriented intervention framework integrating computer vision, mobile imaging, and behavioral cognition is proposed to establish a continuous service loop linking screening, awareness enhancement, intervention, and feedback. The framework transforms conventional one-time posture assessment into an integrated health management process by combining visualized risk communication with personalized behavioral guidance. The proposed design not only improves parental health awareness and participation but also enhances the effectiveness of long-term skeletal posture management. Furthermore, it provides a practical reference for intelligent healthcare systems employing electromagnetic imaging, wireless information transmission, and AI-driven visual perception technologies in rural public health applications.
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