Abstract

This study proposes a novel approach to monitor the fatigue levels of construction rebar benders by measuring chemical biomarkers using sweat sensors. Fatigue resulting from dehydration and energy depletion can severely endanger the safety and health of construction workers. Sodium, lactate, glucose, and sweat rate were chosen as detectable biomarkers in this study, as their concentrations can indicate hydration status, energy consumption, and electrolyte balance, making them suitable for fatigue monitoring. The results were used to construct a fatigue model using supervised machine learning approaches. Construction rebar experiments were conducted while the sweat-based biosensors were applied to rebar workers to evaluate their fatigue with five different classifiers, demonstrating accuracy rates ranging from 71.43% to 96.43%. The results suggested that sweat-based biomarkers offer a noninvasive and accessible fatigue monitoring alternative. This can potentially help alleviate fatigue-related adverse ill effects like dehydration or cramping by enabling instant fluid or nutrient supply recommendations during construction manual tasks. It also provides valuable insights into the physiological effects of rebar work. Besides, this study presents a valuable model for predicting workers’ fatigue levels, which could be applied in the construction industry to improve workers’ safety and productivity. Furthermore, the study highlights the importance of maintaining appropriate hydration, nutrition, and electrolyte balance during physically demanding tasks like construction manual work.

Practical Applications

The study demonstrates that sweat biomarkers, including sweat rate, sodium, lactate, and glucose, can be utilized to assess fatigue among construction rebar workers. Sweat biosensors offer advantages of small size and non-invasiveness, making them suitable for a wide range of scenarios in both the construction industry and sports fields. Moreover, sweat rate and sodium levels can indicate hydration status, and their measurements can be used to recommend immediate fluid intake. Also, lactate and glucose are essential resources that sustain the body, and their measurements can suggest appropriate nutritional intake. These instant recommendations can alleviate the adverse effects of fatigue, consequently reducing fatigue levels. Thus, it is a promising methodology for enhancing the health and safety of the construction industry. In addition, the results of the study will be shared with construction companies, allowing them to introspect fatigue development and chalk out further interventions and policies to manage fatigue effectively.

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Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

The authors acknowledge the following two funding grants: the General Research Fund (GRF) Grant (15201621) titled “Monitoring and managing fatigue of construction plant and equipment operators exposed to prolonged sitting”; and the General Research Fund (GRF) Grant (15210720) titled “The development and validation of a noninvasive tool to monitor mental and physical stress in construction workers.”

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Journal of Construction Engineering and Management
Volume 149Issue 9September 2023

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Received: Oct 12, 2022
Accepted: Apr 18, 2023
Published online: Jun 19, 2023
Published in print: Sep 1, 2023
Discussion open until: Nov 19, 2023

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Ph.D. Candidate, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. ORCID: https://orcid.org/0000-0002-0827-3842. Email: [email protected]
Chair Professor, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. ORCID: https://orcid.org/0000-0002-3187-9041. Email: [email protected]
Xinge Yu, Ph.D. [email protected]
Associate Professor, Dept. of Biomedical Engineering, City Univ. of Hong Kong, Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Ph.D. Candidate, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong (corresponding author). ORCID: https://orcid.org/0000-0002-7274-8195. Email: [email protected]
Bo Fang, Ph.D. [email protected]
Research Assistant Professor, School of Fashion and Textiles, The Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Ph.D. Candidate, Dept. of Applied Physics, The Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Xingcan Huang [email protected]
Ph.D. Candidate, Dept. of Biomedical Engineering, City Univ. of Hong Kong, Hung Hom, Kowloon 999077, Hong Kong. Email: [email protected]
Research Assistant Professor, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hung Hom, Kowloon 999077, Hong Kong. ORCID: https://orcid.org/0000-0003-3187-8062. Email: [email protected]
Xuejiao Xing, Ph.D. [email protected]
Associate Professor, School of Finance, Zhongnan Univ. of Economics and Law, Wuhan 430073, China. Email: [email protected]

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