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Upper limb joint angle measurement in occupational health
Diego Álvarez1, Juan C Alvarez1, Rafael C González1
1a SiMuR Lab, Department of Electrical and Computer Engineering , University of Oviedo , Viesques, Ed. 2, 33204 , Gijón , Spain.
Computer Methods in Biomechanics and Biomedical Engineering
|January 10, 2015
Summary
This study introduces a new wearable sensor system for measuring joint angles during daily activities. The method accurately tracks worker movements to help reduce workplace injuries and associated costs.
Area of Science:
- Biomechanics
- Human Motion Analysis
- Occupational Health Technology
Background:
- Traditional motion capture systems require controlled environments, limiting their use in real-world occupational health assessments.
- Accurate measurement of worker movements is crucial for reducing injury-related costs and improving workplace safety.
Purpose of the Study:
- To develop and validate a novel method for joint angle measurement using wearable sensors suitable for daily life monitoring.
- To enable accurate, long-term estimation of joint angles without drift for occupational health applications.
Main Methods:
- Combined inertial sensors (accelerometers, gyroscopes) and magnetic sensors for joint angle estimation.
- Developed algorithms to avoid numerical integration, preventing angle estimation drift over time.
- Estimated key joint angles including wrist (flexion, lateral deviation), elbow (flexion, pronation), and shoulder (flexion, abduction, internal rotation).
Main Results:
- Laboratory tests demonstrated mean estimation errors between 0.06° and 1.05°.
- Standard deviations in laboratory tests ranged from 2.18° to 9.20°.
- Field tests corroborated laboratory findings in environments free from ferromagnetic interference.
Conclusions:
- The proposed sensor fusion method provides accurate joint angle measurements for real-world occupational health monitoring.
- The drift-free algorithm enables reliable, long-term assessment of worker movements in daily life.
- This technology has the potential to significantly improve injury prevention strategies in occupational settings.
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