Advanced Technologies and Materials

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Vol. 50 No. 2 (2025)
Original articles

Design and Evaluation of a Smart Insole System for RealTime Gait and Plantar Pressure Monitoring

Dejan Movrin
University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia
Surapong Chatpun
Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Thailand
Mitar Simić
University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia
Thanita Sanghan
Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Thailand

Published 2025-12-18

abstract views: 0 // Full text article: 0


Keywords

  • 3D-printed smart insoles,
  • wearable sensors,
  • force-sensitive resistors,
  • gait analysis

How to Cite

Movrin, D., Chatpun, S., Simić, M., & Sanghan, T. (2025). Design and Evaluation of a Smart Insole System for RealTime Gait and Plantar Pressure Monitoring. Advanced Technologies and Materials, 50(2), 31–37. https://doi.org/10.24867/ATM-2025-2-005

Abstract

Wearable sensor systems offer new opportunities for continuous, non-invasive monitoring of gait and plantar pressure, providing insights for rehabilitation and mobility assessment. This study presents a lightweight, minimally intrusive smart insole system integrating five force-sensitive resistors, microcontroller-based readout electronics with Bluetooth low energy communication, and a smartphone application for data visualization, storage, and analysis. The microcontroller (nRF52840) samples force sensitive resistor (FSR) signals at 100 Hz, transmits data wirelessly, and is powered by a rechargeable lithium-ion battery housed in a compact 3D-printed enclosure designed for minimal impact on user comfort and mobility. To assess the influence of insole material on sensor performance, testing was conducted using direct sensor insoles and 3D-printed thermoplastic polyurethane (TPU) insoles of two hardness levels (95A and 65A Shore). Results from a subject walking along a defined path demonstrate consistent trends between left and right insoles, while the measured analog-to-digital converter (ADC) signals indicate that softer insole materials reduce peak sensor readings. The proposed system provides a versatile platform for real-time gait monitoring and personalized gait rehabilitation, highlighting the critical interplay between insole material properties and sensor performance.

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