Electroencephalography (EEG) for psychological hazards and mental health in construction safety automation: Algorithmic Systematic Review (ASR)
Haytham H. Elmousalami, Felix Kin Peng Hui, Lu Aye
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.