A Study of Construction Workers’ Hazard Recognition Process Based on EEG Experiment

Zhiyu Zhang, Zhikun Ding () and Weilin Chen
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Zhiyu Zhang: Shenzhen University
Zhikun Ding: Shenzhen University
Weilin Chen: Shenzhen University

A chapter in Proceedings of the 26th International Symposium on Advancement of Construction Management and Real Estate, 2022, pp 1441-1453 from Springer

Abstract: Abstract As a labour-intensive industry, the casualties caused by safety accidents in the construction industry have always been at the forefront of all industries. Most safety accidents during the construction process are attributed to workers themselves, so how to effectively reduce the accidents caused by construction workers has become an important issue for the construction safety management. Among them, the process of construction workers’ subjective risk perception is the key to change their behaviour and decision-making. Thus, this article is based on the related concepts of construction engineering hazard identification and neuromanagement. Use EEG to do event-related potential experiments to study the process of construction workers’ hazard identification. Then conduct an objective analysis of the experimental results. It is found that individuals produce more significant P200 and LPP waveform in the process of risk identification, and there are significant differences in the P200 amplitudes produced by different types of dangerous stimuli. At the same time, the experimental results showed that, before the individual was stimulated by the dangerous pictures, the brain will perform two-stage processing, that is, the early perception of emergencies and the subjective risk level judgment. In summary, it showed that the cross-application of neuroscience in the engineering field can open up new fields for research and conduct deeper explorations. At the same time, it further confirms the importance of human factors in the study of construction safety-related issues.

Keywords: Hazard identification; Cognitive behaviour; Construction workers; EEG; ERP; P200 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/978-981-19-5256-2_111

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