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Abbasnejad, B, Nasirian, A, Duan, S, Diro, A, Prasad Nepal, M and Song, Y (2024) Measuring BIM implementation: A mathematical modeling and artificial neural network approach. Journal of Construction Engineering and Management, 150(05).
Asadian, E, Azeez, S, Leicht, R M and Asadi, S (2024) Exploring the barriers to women in construction and the opportunities presented through lean. Journal of Construction Engineering and Management, 150(05).
Henao, Y, Grubert, E, Korey, M, Bank, L C and Gentry, R (2024) Life cycle assessment and life cycle cost analysis of repurposing decommissioned wind turbine blades as high-voltage transmission poles. Journal of Construction Engineering and Management, 150(05).
Huang, Y, Liu, D, Bell, F M, Yu, J and Pena-Mora, F (2024) Influences of intra- and interorganizational IT innovations on knowledge sharing and team creativity: Evidence from construction projects in China. Journal of Construction Engineering and Management, 150(05).
Min, Y and Lee, H W (2024) Adoption inequalities and causal relationship between residential electric vehicle chargers and heat pumps. Journal of Construction Engineering and Management, 150(05).
Nabi, M A, El-Adaway, I H and Assaad, R H (2024) Modeling inflation transmission among different construction materials. Journal of Construction Engineering and Management, 150(05).
Nguyen, P H D and Tran, D (2024) Exploring the use of quality control plans for alternative contracting methods in highway projects. Journal of Construction Engineering and Management, 150(05).
Ning, X, Ye, X, Li, H, Rajendra, D and Skitmore, M (2024) Evolutionary game analysis of optimal strategies for construction stakeholders in promoting the adoption of green building technology innovation. Journal of Construction Engineering and Management, 150(05).
Shi, M, Chen, C, Xiao, B and Seo, J (2024) Vision-based detection method for construction site monitoring by integrating data augmentation and semisupervised learning. Journal of Construction Engineering and Management, 150(05).
Tao, Y, Hu, H, Xu, F and Zhang, Z (2024) Work-rest schedule optimization of precast production considering workers' overexertion. Journal of Construction Engineering and Management, 150(05).
Turkoglu, H, Arditi, D and Polat, G (2024) Augmented time-cost trade-off optimization using particle swarm optimization. Journal of Construction Engineering and Management, 150(05).
Wang, H, Xu, S, Cui, D, Xu, H and Luo, H (2024) Information integration of regulation texts and tables for automated construction safety knowledge mapping. Journal of Construction Engineering and Management, 150(05).
Wang, J, Liang, M and Liao, P C (2024) Toward an intuitive device for construction hazard recognition management: Eye fixation-related potentials in reinvestigation of hazard recognition performance prediction. Journal of Construction Engineering and Management, 150(05).
- Type: Journal Article
- Keywords: electroencephalogram; eye fixation-related potentials; hazard recognition performance; power spectral density; psychological mechanisms; time-frequency representation
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-13675
- Abstract:
Developing real-Time automatic intuitive devices based on electroencephalography (EEG) to improve hazard recognition performance (HRP) is essential in construction engineering management. However, existing studies generally developed devices based on unimodal data, failing to distinguish the role played by brain activities in different visual areas and ignoring the possible existence of other psychological mechanisms. Therefore, this study aims to use multimodal data based on brain-eye synergy to predict HRP and reveal the cognitive mechanism of hazard recognition to develop intuitive hazard recognition devices. Accordingly, we designed experiments to investigate this problem: (1) 53 construction workers completed a 120-Trial hazard recognition task in a laboratory environment (N=6,360), (2) an EEG recorder collected the participants' EEG activities and an eye-Tracking device recorded the data of eye movement, and (3) the power spectral density (PSD) of EEG was calculated and then imported into Matlab2018a in combination with EEGLAB for analysis. The results showed that the prediction results of hazard recognition have a time-variant effect. For fall-related hazards, EEG signals within 0-320 ms after the onset were significant in predicting HRP; for electric-related and fire-related hazards, EEG signals within 560-640 ms after the starting point were the most valuable. Also, compared with fall-related hazards, it took a significantly longer time to recognize electric-related and fire-related hazards, which consumed more attentional resources. Finally, the frontal lobe requires more attentional resources to finish cognitive activities than the occipital lobe to finish visual information processing activities, and the occipital lobe needs to process visual information first, and then transmit it to the frontal lobe for analysis and judgment. For the body of knowledge, this study, finding the time-variant effect of HRP, improves the theory of construction hazard recognition from an eye-brain synergy perspective and provides guidance for developing intuitive hazard recognition devices and improving management performance.
Wang, L, Lee, J, Nimawat, J, Han, K and Gupta, A (2024) Integrated 4D design change management model for construction projects. Journal of Construction Engineering and Management, 150(05).
Wang, S, Hasan, M and Lu, M (2024) Global sensitivity analysis methodology for construction simulation models: Multiple linear regressions versus multilayer perceptions. Journal of Construction Engineering and Management, 150(05).
Zhang, S, Hua, X and Shi, X (2024) Measurement for risk perception ability. Journal of Construction Engineering and Management, 150(05).