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Related Experiment Video

Updated: Jul 23, 2025

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
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IoT System for Real-Time Posture Asymmetry Detection.

Monica La Mura1, Marco De Gregorio1, Patrizia Lamberti1

  • 1Department of Information and Electrical Engineering and Applied Mathematics, University of Salerno, 84084 Fisciano, SA, Italy.

Sensors (Basel, Switzerland)
|July 11, 2023
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Summary
This summary is machine-generated.

This study introduces a low-cost Internet of Things (IoT) system to monitor sitting posture. It alerts workers to asymmetric positions, helping prevent musculoskeletal disorders.

Keywords:
IoTdigital healthforce sensing resistors (FSR)monitoringposturereal-time

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Area of Science:

  • Biomedical Engineering
  • Human-Computer Interaction
  • Occupational Health

Background:

  • Musculoskeletal disorders are common among computer workers due to prolonged incorrect sitting postures.
  • Internet of Things (IoT) systems offer potential for health monitoring in smart environments.
  • Existing solutions may lack cost-effectiveness or real-time feedback for posture correction.

Purpose of the Study:

  • To propose and evaluate a low-cost IoT measurement system for monitoring sitting posture symmetry.
  • To provide real-time visual alerts to workers exhibiting asymmetric sitting positions.
  • To record sitting behavior data for further analysis and intervention development.

Main Methods:

  • Development of a cushion embedded with four force sensing resistors (FSRs).
  • Implementation of a microcontroller-based circuit for sensor data acquisition.
  • Utilization of Java-based software for real-time monitoring and an uncertainty-driven asymmetry detection algorithm.
  • Integration with a web database for logging posture shifts.

Main Results:

  • The system successfully detects shifts between symmetric and asymmetric sitting postures.
  • Real-time visual pop-up alerts are generated to notify the worker of asymmetric positions.
  • Posture shift data is logged for subsequent analysis of sitting behavior patterns.

Conclusions:

  • The developed IoT system offers a practical and low-cost solution for monitoring and improving sitting posture.
  • Real-time alerts can prompt workers to adjust their posture, potentially reducing the risk of musculoskeletal disorders.
  • The system's data logging capability supports further research into ergonomic interventions and workplace health.