Electroencephalography (EEG) for psychological hazards and mental health in construction safety automation: Algorithmic Systematic Review (ASR)

This algorithmic systematic review investigates the applications of electroencephalography (EEG) for recognizing psychological hazards and monitoring mental health in construction safety. As automation and wearable technologies gain traction, EEG systems provide real-time insights into workers' cognitive and emotional states, helping to identify stress, fatigue, and safety risks. Utilizing a structured search algorithm, literature from Scopus and Web of Science was filtered and analysed to create a comprehensive framework for EEG deployment in five key domains: automated psychological and cognitive assessment, hazard recognition and safety decision-making, advanced technology integration, situational awareness enhancement, and sustainability contributions. The review underscores the synergy of EEG with robotics, virtual reality, and wearable devices, enhancing safety management in construction. Challenges such as data privacy and scalability are thoroughly examined. This paper significantly advances the understanding of EEG's role in construction automation, offering future research directions to optimize EEG-based systems for a safer, more sustainable construction industry. • EEG enables automated real-time monitoring of construction psychological hazards. • Advances intelligent, sustainable safety management in construction through automation. • Five key domains of EEG applications in construction safety automation were identified. • Integration of EEG with robotics and VR enhances hazard recognition and awareness. • Key challenges like data privacy and scalability addressed for EEG system deployment.

Authors

Publication Details

Journal
Automation in Construction
Published
2025-06-27
DOI
https://doi.org/10.1016/j.autcon.2025.106346
Citations
10
Primary Topic
Occupational Health and Safety Research
Type
article
Field-Weighted Citation Impact
15.40

Funders

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article

Electroencephalography (EEG) for psychological hazards and mental health in construction safety automation: Algorithmic Systematic Review (ASR)

Haytham H. Elmousalami, Lu Aye, Felix Kin Peng Hui
10 citations
Automation in Construction
Occupational Health and Safety Research
15.40
article

Electroencephalography (EEG) for psychological hazards and mental health in construction safety automation: Algorithmic Systematic Review (ASR)

Haytham H. Elmousalami, Lu Aye, Felix Kin Peng Hui
article en
10 citations

Abstract

This algorithmic systematic review investigates the applications of electroencephalography (EEG) for recognizing psychological hazards and monitoring mental health in construction safety. As automation and wearable technologies gain traction, EEG systems provide real-time insights into workers' cognitive and emotional states, helping to identify stress, fatigue, and safety risks. Utilizing a structured search algorithm, literature from Scopus and Web of Science was filtered and analysed to create a comprehensive framework for EEG deployment in five key domains: automated psychological and cognitive assessment, hazard recognition and safety decision-making, advanced technology integration, situational awareness enhancement, and sustainability contributions. The review underscores the synergy of EEG with robotics, virtual reality, and wearable devices, enhancing safety management in construction. Challenges such as data privacy and scalability are thoroughly examined. This paper significantly advances the understanding of EEG's role in construction automation, offering future research directions to optimize EEG-based systems for a safer, more sustainable construction industry. • EEG enables automated real-time monitoring of construction psychological hazards. • Advances intelligent, sustainable safety management in construction through automation. • Five key domains of EEG applications in construction safety automation were identified. • Integration of EEG with robotics and VR enhances hazard recognition and awareness. • Key challenges like data privacy and scalability addressed for EEG system deployment.

Automation in ConstructionVol. 177
University of Melbourne
Sustainable cities and communities
Openalex Percentile: Top 1%
Occupational Health and Safety Research
15.40
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