Advanced Technologies and Materials

 

GUIDE FOR AUTHORS SUBMIT MANUSCRIPT
Vol. 50 No. 2 (2025)
Original articles

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

Dejan Movrin
https://orcid.org/0000-0001-7812-0713 (unauthenticated) University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia
Surapong Chatpun
https://orcid.org/0000-0002-6888-5170 (unauthenticated) Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Thailand
Mitar Simić
https://orcid.org/0000-0002-8300-022X (unauthenticated) University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia
Thanita Sanghan
https://orcid.org/0009-0005-1693-5673 (unauthenticated) Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Thailand

DOI

Published 2025-12-18

Keywords

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

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.