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Abdelkader, E M, Moselhi, O, Marzouk, M and Zayed, T (2021) Integrative Evolutionary-Based Method for Modeling and Optimizing Budget Assignment of Bridge Maintenance Priorities. Journal of Construction Engineering and Management, 147(09).
Ahmed, A, Mohammed, H A, Gambatese, J and Hurwitz, D (2021) Effects of Flashing Blue Lights Mounted on Paving Equipment on Vehicle Speed Behavior in Work Zones. Journal of Construction Engineering and Management, 147(09).
Cai, Q, Hu, Q and Ma, G (2021) Improved Hybrid Reasoning Approach to Safety Risk Perception under Uncertainty for Mountain Tunnel Construction. Journal of Construction Engineering and Management, 147(09).
Chen, B, Yu, X, Dong, F, Zheng, C, Ding, G and Wu, W (2021) Compaction Quality Evaluation of Asphalt Pavement Based on Intelligent Compaction Technology. Journal of Construction Engineering and Management, 147(09).
Hajj, C E, Jawad, D and Montes, G M (2021) Analysis of a Construction Innovative Solution from the Perspective of an Information System Theory. Journal of Construction Engineering and Management, 147(09).
Hasan, A, Rameezdeen, R, Baroudi, B and Ahn, S (2021) Mobile ICT–Induced Informal Work in the Construction Industry: Boundary Management Approaches and Consequences. Journal of Construction Engineering and Management, 147(09).
Hassan, F u, Le, T and Lv, X (2021) Addressing Legal and Contractual Matters in Construction Using Natural Language Processing: A Critical Review. Journal of Construction Engineering and Management, 147(09).
Huang, H, Zhang, C and Hammad, A (2021) Effective Scanning Range Estimation for Using TLS in Construction Projects. Journal of Construction Engineering and Management, 147(09).
Jiang, Y and Bai, Y (2021) Low–High Orthoimage Pairs-Based 3D Reconstruction for Elevation Determination Using Drone. Journal of Construction Engineering and Management, 147(09).
Johannes, K, Theodorus Voordijk, J, Marias Adriaanse, A and Aranda-Mena, G (2021) Identifying Maturity Dimensions for Smart Maintenance Management of Constructed Assets: A Multiple Case Study. Journal of Construction Engineering and Management, 147(09).
Kar, S and Jha, K N (2021) Exploring the Critical Barriers to and Enablers of Sustainable Material Management Practices in the Construction Industry. Journal of Construction Engineering and Management, 147(09).
Noghabaei, M, Han, K and Albert, A (2021) Feasibility Study to Identify Brain Activity and Eye-Tracking Features for Assessing Hazard Recognition Using Consumer-Grade Wearables in an Immersive Virtual Environment. Journal of Construction Engineering and Management, 147(09).
- Type: Journal Article
- Keywords: Virtual reality; Electroencephalograph (EEG); Eye tracking; Safety training; Brain sensing;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002130
- Abstract:
Hazard recognition is vital to achieving effective safety management. Unmanaged or unrecognized hazards on construction sites can lead to unexpected accidents. Recent research has identified cognitive failures among workers as being a principal factor associated with poor hazard recognition levels. Therefore, understanding cognitive correlates of when individuals recognize hazards versus when they fail to recognize hazards will be useful in combating poor hazard recognition. Such efforts are now possible with recent advances in electroencephalograph (EEG) and eye-tracking technologies. This paper presents a feasibility study that combines EEG and eye tracking in an immersive virtual environment (IVE) to predict when safety hazards will be successfully recognized during hazard recognition efforts using machine learning techniques. Workers wear a virtual reality (VR) head-mounted device (HMD) that is equipped with an eye-tracking sensor. Together with an EEG sensor, brain activities and eye movements are recorded as the workers navigate a simulated virtual construction site and recognize safety hazards. Through an experiment and a feature extraction and selection process, 13 best features out of 306 features from EEG and eye tracking were selected to train a machine learning model. The results show that EEG and eye tracking together can be leveraged to predict when individuals will recognize safety hazards. The developed IVE can be potentially used to first identify hazard types that are correlated with higher arousal and valence. Also, the developed IVE can be potentially used to evaluate the correlation among arousal, valence, and hazard recognition.
Perez-Perez, Y, Golparvar-Fard, M and El-Rayes, K (2021) Scan2BIM-NET: Deep Learning Method for Segmentation of Point Clouds for Scan-to-BIM. Journal of Construction Engineering and Management, 147(09).
Raoufi, M and Fayek, A R (2021) How to Improve Crew Motivation and Performance on Construction Sites. Journal of Construction Engineering and Management, 147(09).
Taghizadeh, K, Alizadeh, M and Yavari Roushan, T (2021) Cooperative Game Theory Solution to Design Liability Assignment Issues in BIM Projects. Journal of Construction Engineering and Management, 147(09).
Votto, R, Lee Ho, L and Berssaneti, F (2021) Earned Duration Management Control Charts: Role of Control Limit Width Definition for Construction Project Duration Monitoring. Journal of Construction Engineering and Management, 147(09).
Xu, Y, Shen, X, Lim, S and Li, X (2021) Three-Dimensional Object Detection with Deep Neural Networks for Automatic As-Built Reconstruction. Journal of Construction Engineering and Management, 147(09).