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AI-Assisted Insole Sensing System for Multifunctional Plantar-Healthcare Applications.

Kaiyuan Xiang1,2,3, Mengjie Liu1,2, Jun Chen1,2

  • 1Department of Psychology, Faculty of Arts and Sciences, Beijing Normal University, Zhuhai 519087, China.

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Summary

A new intelligent insole uses polymer optical fibers (S-POF) for cost-effective, real-time gait monitoring. This wearable system accurately analyzes pressure, cadence, and gait patterns, offering a promising solution for remote health and rehabilitation.

Keywords:
artificial intelligencegait monitoringpolymer materialsmart healthcaresmartphone

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Area of Science:

  • Biomedical Engineering
  • Materials Science
  • Wearable Technology

Background:

  • Global population aging increases demand for health monitoring.
  • Current wearable devices have limitations like electromagnetic radiation, complexity, and high cost.
  • Need for advanced, accessible gait monitoring solutions.

Purpose of the Study:

  • Develop a cost-effective, portable, and real-time intelligent insole sensing system for gait monitoring.
  • Utilize Solaris silicone rubber-integrated PMMA polymer optical fiber (S-POF) for pressure sensing.
  • Enable remote health monitoring and improve rehabilitation outcomes.

Main Methods:

  • Integrated S-POF into an intelligent insole for pressure-to-light intensity conversion.
  • Developed a multichannel multiplexing framework for smartphone integration.
  • Employed AI models for gait pattern recognition and analysis of gait phases.

Main Results:

  • Achieved high correlation coefficients (0.995, 0.952, 0.910) for pressure sensing.
  • Demonstrated excellent durability (4.8% variation after 10,000 cycles) and water/temperature resistance.
  • Obtained high accuracy (96.87%) in gait pattern recognition with low errors (4.16% STP, 6.25% SWP) for gait phase analysis.

Conclusions:

  • The S-POF intelligent insole system offers a portable, cost-effective, and accurate solution for real-time gait monitoring.
  • The system's durability, water resistance, and smartphone compatibility enhance its daily care utility.
  • Promising potential for advancing rehabilitation and healthcare through intelligent gait analysis and pattern recognition.