Automated and Continuous Fatigue Monitoring in Construction Workers Using Forearm EMG and IMU Wearable Sensors and...

Area of Science:

• Occupational Health
• Biomedical Engineering
• Ergonomics

Background:

• Construction workers experience high fatigue levels (approx. 40% in the US), leading to safety risks, reduced productivity, and lower work quality.
• Current fatigue detection methods lack a standardized approach due to the complex nature of fatigue.
• Continuous fatigue monitoring is crucial for mitigating adverse effects and preventing long-term health issues in the construction workforce.

Purpose of the Study:

• To develop and validate a system for continuous worker fatigue monitoring.
• To predict the aerobic fatigue threshold (AFT) using forearm muscle activity and motion data.
• To assess the effectiveness of the proposed system in identifying fatigue levels in construction workers.

Main Methods:

• A five-module system was developed: data acquisition, activity recognition, oxygen uptake prediction, maximum aerobic capacity (MAC) estimation, and continuous AFT monitoring.
• Forearm muscle activity and motion data were utilized for fatigue assessment.
• The system was evaluated on participants performing fourteen scaffold-building activities.

Main Results:

• The AFT features demonstrated high accuracy (92.31%) in assessing worker fatigue levels.
• This accuracy significantly outperformed traditional metrics like heart rate (51.28%) and percentage heart rate reserve (50.43%).
• The overall system performance on unseen data, using average two-minute AFT features, reached 76.74%.

Conclusions:

• The study validates the feasibility of using forearm muscle activity and motion data for continuous worker fatigue monitoring.
• The proposed system offers a more accurate and objective method for assessing fatigue compared to existing measures.
• Implementing this system can help improve safety, productivity, and long-term health in the construction industry.