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Updated: Jun 13, 2025

Home-Based Monitor for Gait and Activity Analysis
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IoT-Based Wireless System for Gait Kinetics Monitoring in Multi-Device Therapeutic Interventions.

Christian Lang Rathke1, Victor Costa de Andrade Pimentel2,3, Pablo Javier Alsina2

  • 1Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Macaíba 59280-000, RN, Brazil.

Sensors (Basel, Switzerland)
|September 14, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces an affordable IoT gait analysis system using insole pressure sensors. The system shows strong correlation with gold standards, suggesting potential for gait disorder assessment.

Keywords:
Internet of ThingsMQTT protocolbiomechanical sensorsgait analysissmart insoles

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Area of Science:

  • Biomedical Engineering
  • Wearable Technology
  • Biomechanics

Background:

  • Gait analysis is crucial for assessing and monitoring neurological and musculoskeletal disorders.
  • Existing gait analysis systems can be expensive and lack portability.
  • There is a need for cost-effective and accessible gait assessment tools.

Purpose of the Study:

  • To develop and validate an Internet of Things (IoT)-based gait analysis system using insole pressure sensors.
  • To assess the correlation and agreement between the developed insole system and a gold-standard gait analysis system.
  • To explore the potential of piezoresistive sensors for gait kinetics measurement.

Main Methods:

  • An IoT system was developed using piezoresistive pressure sensors integrated into a left foot insole.
  • Data acquisition was performed using an ESP32 board communicating via Wi-Fi and an MQTT framework.
  • A comparative analysis was conducted against the Zeno system (gold standard) with four healthy volunteers over a 10m path.

Main Results:

  • A strong positive correlation (r = 0.87) was observed between the insole system and the reference system for vertical ground reaction force (vGRF).
  • Bland-Altman analysis revealed a minimal mean difference (0.011), indicating good agreement with a slight bias.
  • The IoT communication framework demonstrated reliable functionality.

Conclusions:

  • The developed IoT-based insole pressure sensor system shows promise as a cost-effective tool for gait analysis.
  • Piezoresistive sensors offer a viable solution for gait disorder assessment and monitoring.
  • Further validation with larger sample sizes is necessary to confirm clinical and research reliability, considering operational factors like temperature and sensor placement.