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

Jinjing Ke, Ming Zhang, Xiaowei Luo*, Jiayu Chen

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

84 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number103598
JournalAutomation in Construction
Volume125
Online published11 Feb 2021
DOIs
Publication statusPublished - May 2021

Funding

This work was jointly supported by the National Natural Science Foundation of China Grant # 51778553 , Research Grants Council, University Grants Committee of the Hong Kong Special Administrative Region , No. CityU 20206415 , and City University of Hong Kong Strategic Research Grant # 7005240 . The conclusions herein are those of the authors and do not necessarily reflect the views of the sponsoring agencies.

Research Keywords

  • EEG
  • Hazards identification
  • Noise-induced distraction
  • Sustained attention

Fingerprint

Dive into the research topics of 'Monitoring distraction of construction workers caused by noise using a wearable Electroencephalography (EEG) device'. Together they form a unique fingerprint.

Cite this