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Integrating sEMG and IMU Sensors in an e-Textile Smart Vest for Forward Posture Monitoring: First Steps
João Martins1, Sara M Cerqueira1, André Whiteman Catarino2
1Center for Microelectromechanical Systems (CMEMS), University of Minho, 4800-058 Guimarães, Portugal.
Sensors (Basel, Switzerland)
|July 27, 2024
Summary
This study introduces a novel wearable device for real-time forward head posture (FHP) monitoring, integrating electromyography and inertial sensors with e-textiles. The system demonstrates high accuracy, outperforming traditional methods for posture assessment.
Area of Science:
- Biomedical Engineering
- Wearable Technology
- Rehabilitation Technology
Background:
- The increasing prevalence of forward head posture (FHP) necessitates advanced monitoring solutions.
- Wearable devices offer a promising avenue for continuous health assessment, including posture analysis.
Purpose of the Study:
- To develop and validate a wearable system for real-time FHP assessment.
- To explore the use of e-textiles for improved wearable device integration and performance.
Main Methods:
- Integration of cervical electromyographic (EMG) signals and inertial measurement unit (IMU) data.
- Development of e-textile surface electrodes and conductive tracks for enhanced wearability.
- Benchmarking of sEMG hardware and textile electrodes against gold standards.
- Validation of the posture monitoring module using a robotic arm.
Main Results:
- Imbut's Elitex fiber demonstrated superior tensile strength and abrasion resistance compared to Shieldex fibers.
- The developed textile electrodes achieved a lower root mean square error (RMSE) (10.02%) than commercial Ag/AgCl electrodes (11.11%) in sEMG acquisition.
- The posture monitoring module achieved an overall error of 4.77° in joint angle estimation.
Conclusions:
- The proposed wearable device effectively assesses forward head posture using integrated EMG and IMU data.
- E-textiles provide a viable solution for creating comfortable and effective wearable posture monitoring systems.
- The system shows potential for clinical applications in diagnosing and managing FHP.

