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Selection of wearable sensor measurements for monitoring and managing entry-level construction worker fatigue: a logistic regression approach

Wonil Lee (Safety and Health Assessment and Research for Prevention (SHARP) Program, Washington State Department of Labor and Industries, Olympia, Washington, USA)
Ken-Yu Lin (Department of Construction Management, College of Built Environments, University of Washington, Seattle, Washington, USA)
Peter W. Johnson (Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, USA)
Edmund Y.W. Seto (Department of Environmental and Occupational Health Sciences, School of Public Health, University of Washington, Seattle, Washington, USA)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 1 July 2021

Issue publication date: 16 August 2022

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Abstract

Purpose

The identification of fatigue status and early intervention to mitigate fatigue can reduce the risk of workplace injuries. Off-the-shelf wearable sensors capable of assessing multiple parameters are available. However, using numerous variables in the fatigue prediction model can elicit data issues. This study aimed at identifying the most relevant variables for measuring occupational fatigue among entry-level construction workers by using common wearable sensor technologies, such as electrocardiogram and actigraphy sensors.

Design/methodology/approach

Twenty-two individuals were assigned different task workloads in repeated sessions. Stepwise logistic regression was used to identify the most parsimonious fatigue prediction model. Heart rate variability measurements, standard deviation of NN intervals and power in the low-frequency range (LF) were considered for fatigue prediction. Fast Fourier transform and autoregressive (AR) analysis were employed as frequency domain analysis methods.

Findings

The log-transformed LF obtained using AR analysis is preferred for daily fatigue management, whereas the standard deviation of normal-to-normal NN is useful in weekly fatigue management.

Research limitations/implications

This study was conducted with entry-level construction workers who are involved in manual material handling activities. The findings of this study are applicable to this group.

Originality/value

This is the first study to investigate all major measures obtainable through electrocardiogram and actigraphy among current mainstream wearables for monitoring occupational fatigue in the construction industry. It contributes knowledge on the use of wearable technology for managing occupational fatigue among entry-level construction workers engaged in material handling activities.

Keywords

Acknowledgements

This article is written based on the first author’s master’s thesis in the School of Public Health program at the University of Washington, United States, Lee (2018).

Citation

Lee, W., Lin, K.-Y., Johnson, P.W. and Seto, E.Y.W. (2022), "Selection of wearable sensor measurements for monitoring and managing entry-level construction worker fatigue: a logistic regression approach", Engineering, Construction and Architectural Management, Vol. 29 No. 8, pp. 2905-2923. https://doi.org/10.1108/ECAM-02-2021-0106

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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