Smart Data-Driven Architecture for Healthcare Information Analysis

Abstract

This study presents an intelligent data-driven framework for foot and ankle health assessment and personalized orthopedic product design. The system integrates multimodal clinical data—including three-dimensional foot scanning, dynamic gait analysis, and plantar pressure detection—to construct a comprehensive medical database for diagnosis and treatment of foot and ankle disorders. By combining biomechanical modeling with a modular knowledge base, the framework supports parametric customization of orthopedic footwear and corrective devices. A doctor-patient collaborative platform enables real-time data interaction, structured medical reporting, and cross-institutional data sharing. Experimental deployment involving 1,820 clinical samples demonstrated the system’s capability to achieve precise biomechanical adaptation, reduce diagnosis and treatment cycles, and enhance product design accuracy. The proposed framework provides a scalable and intelligent solution for transforming orthopedic rehabilitation from experience-based to data-driven paradigms, offering significant implications for digital healthcare innovation and precision medicine applications.