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
- Haytham H. Elmousalami (ORCID: https://orcid.org/0000-0002-2032-0648)
- Lu Aye (ORCID: https://orcid.org/0000-0002-5495-1683)
- Felix Kin Peng Hui (ORCID: https://orcid.org/0000-0002-4800-9130)
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
- University of Melbourne