Monitoring distraction of construction workers caused by noise using a wearable Electroencephalography (EEG) device

In the construction environment with high attention requirements, distraction is the main cause of unsafe behavior and safety performance degradation. However, few studies have focused on distraction's cognitive features and how to monitor it objectively in the construction workplace. To fill t...

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Veröffentlicht in:Automation in construction 2021-05, Vol.125, p.103598, Article 103598
Hauptverfasser: Ke, Jinjing, Zhang, Ming, Luo, Xiaowei, Chen, Jiayu
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description In the construction environment with high attention requirements, distraction is the main cause of unsafe behavior and safety performance degradation. However, few studies have focused on distraction's cognitive features and how to monitor it objectively in the construction workplace. To fill the research gap, the present study examined the correlation between distraction and brain activity using an Electroencephalography (EEG) device, intending to provide an approach for objectively monitoring worker distraction. In the simulated hazards identification activity, sustained attention to response task and dual-task paradigms have been employed to induce distraction combined with noise interference. Twenty-seven subjects participated in the experiment to identify whether a hazardous opening exists or not in the workplace in the shown images. The EEG waves were recorded and divided into two groups according to task performance: focused and distracted. Through feature calculation and extraction, it was found that beta and gamma powers in the left temporal and right pre-frontal cortex can distinguish these two statuses, particularly in channels T7 and AF4. The indicators can be considered as an objective evaluation of an individual's sustained attention and attention failures. The developed indicators located in specified brain zones can also be used as a reference for attention training. By providing safety managers with attention status about the workers in high-risk workplaces, distraction detection contributes to control and regulate work error and improper operation, which can extend to apply in other attentive jobs like drivers, pilots, surgeons, and lifeguards. •An objective distraction monitoring method is proposed.•EEG frequency features can distinguish focused and distracted state.•Feasibility of distraction monitoring method is validated by SVM classification.•Classification performance of channel T7 and AF4 outperformed other electrodes.
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subjects Brain
Construction & Building Technology
Construction industry
EEG
Electroencephalography
Engineering
Engineering, Civil
Feature extraction
Hazard identification
Hazards identification
Indicators
Monitoring
Noise-induced distraction
Performance degradation
Safety management
Science & Technology
Sustained attention
Technology
Workplaces
title Monitoring distraction of construction workers caused by noise using a wearable Electroencephalography (EEG) device
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