Fatigue analysis of construction workers based on electrocardiogram signals

This study investigates physiological fatigue in construction workers during manual handling tasks using electrocardiogram (ECG) signals and the Borg CR10 scale. Twelve male workers performed repetitive lifting until exhaustion, with ECG data and subjective fatigue scores collected across low, moderate and severe fatigue levels. Results show that as fatigue increases, heart rate variability indicators (standard deviation of RR intervals [SDNN], root mean square of successive differences between adjacent RR intervals [RMSSD]) decrease, while low-frequency power (LF) and heart rate increase significantly. Statistical analysis identifies SDNN, RMSSD, LF and heart rate as four key biomarkers strongly discriminating fatigue levels. These findings reveal dynamic ECG patterns associated with fatigue and provide a theoretical foundation for establishing physiological thresholds and developing wearable monitoring systems for intelligent occupational health management in construction.

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Publication Details

Journal
International Journal of Occupational Safety and Ergonomics
Published
2026-06-09
DOI
https://doi.org/10.1080/10803548.2026.2675826
Primary Topic
Sleep and Work-Related Fatigue
Type
article
Field-Weighted Citation Impact
0.00

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article

Fatigue analysis of construction workers based on electrocardiogram signals

Xiaohong Gui, Mengru Shang, Liang Jiang, Jiye Pei
International Journal of Occupational Safety and Ergonomics
Sleep and Work-Related Fatigue
article

Fatigue analysis of construction workers based on electrocardiogram signals

Xiaohong Gui, Mengru Shang, Liang Jiang, Jiye Pei
article en

Abstract

This study investigates physiological fatigue in construction workers during manual handling tasks using electrocardiogram (ECG) signals and the Borg CR10 scale. Twelve male workers performed repetitive lifting until exhaustion, with ECG data and subjective fatigue scores collected across low, moderate and severe fatigue levels. Results show that as fatigue increases, heart rate variability indicators (standard deviation of RR intervals [SDNN], root mean square of successive differences between adjacent RR intervals [RMSSD]) decrease, while low-frequency power (LF) and heart rate increase significantly. Statistical analysis identifies SDNN, RMSSD, LF and heart rate as four key biomarkers strongly discriminating fatigue levels. These findings reveal dynamic ECG patterns associated with fatigue and provide a theoretical foundation for establishing physiological thresholds and developing wearable monitoring systems for intelligent occupational health management in construction.

International Journal of Occupational Safety and Ergonomics
China University of Mining and Technology (CN)
Fundamental Research Funds for the Central Universities
Decent work and economic growth
Openalex Percentile: Top 4%
Sleep and Work-Related Fatigue
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Fatigue analysis of construction workers based on electrocardiogram signals — Xiaohong Gui, Mengru Shang, et al. · International Journal of Occupational Safety and Ergonomics (2026) | TGRS Research Map | TGRS