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Abubakar, M E, Hasan, A and Jha, K N (2022) Delays and Financial Implications of COVID-19 for Contractors in Irrigation Projects. Journal of Construction Engineering and Management, 148(09).
Adibfar, A and Costin, A M (2022) Creation of a Mock-up Bridge Digital Twin by Fusing Intelligent Transportation Systems (ITS) Data into Bridge Information Model (BrIM). Journal of Construction Engineering and Management, 148(09).
Alqahtani, F K, Alkhaldi, M, Alsaqer, T, Abotaleb, I S, Mohamed, A G and Dirar, S (2022) A Comparative Assessment of Advanced Construction Systems Incorporating Green Concrete. Journal of Construction Engineering and Management, 148(09).
Besaiso, H and Fenn, P (2022) How International Construction Arbitrators Make Their Decisions: Status of Commercial Norms and International Construction Law. Journal of Construction Engineering and Management, 148(09).
Cadenazzi, T, Keles, B, Rahman, M K and Nanni, A (2022) Life-Cycle Cost and Life-Cycle Assessment of a Monumental Fiber-Reinforced Polymer Reinforced Concrete Structure. Journal of Construction Engineering and Management, 148(09).
Cao, Q, Zou, X and Zhang, L (2022) Multiobjective Robust Optimization Model for Generating Stable and Makespan-Protective Repetitive Schedules. Journal of Construction Engineering and Management, 148(09).
Dayan, V, Chileshe, N and Hassanli, R (2022) A Scoping Review of Information-Modeling Development in Bridge Management Systems. Journal of Construction Engineering and Management, 148(09).
Franz, B, Leicht, R, El Asmar, M and Molenaar, K (2022) Methodological Consistency for Quantitative Analysis and Reporting in Project Delivery System Performance Research. Journal of Construction Engineering and Management, 148(09).
García de Soto, B, Turk, Å, Maciel, A, Mantha, B, Georgescu, A and Sonkor, M S (2022) Understanding the Significance of Cybersecurity in the Construction Industry: Survey Findings. Journal of Construction Engineering and Management, 148(09).
Guo, D, Song, Z, Xu, T, Zhang, Y and Ding, L (2022) Coupling Analysis of Tunnel Construction Risk in Complex Geology and Construction Factors. Journal of Construction Engineering and Management, 148(09).
Hasan, A and Kamardeen, I (2022) Occupational Health and Safety Barriers for Gender Diversity in the Australian Construction Industry. Journal of Construction Engineering and Management, 148(09).
Kamma, R C and Jha, K N (2022) Quantifying Building Construction and Demolition Waste Using Permit Data. Journal of Construction Engineering and Management, 148(09).
Lasni, A and Boton, C (2022) Implementing Construction Planning and Control Software: A Specialized Contractor Perspective. Journal of Construction Engineering and Management, 148(09).
Lee, G and Lee, S (2022) Importance of Testing with Independent Subjects and Contexts for Machine-Learning Models to Monitor Construction Workers’ Psychophysiological Responses. Journal of Construction Engineering and Management, 148(09).
- Type: Journal Article
- Keywords: Construction safety; Psychophysiological monitoring; Machine learning; Wearable biosensors; Validation methods; Generalizability;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0002341
- Abstract:
Because workers’ abnormal psychophysiological responses (e.g., high levels of stress and fatigue) are directly or indirectly linked to disorders and accidents at construction sites, monitoring workers’ abnormal psychophysiological responses during ongoing work enables preventive interventions, thereby improving their health and safety. As such, wearable biosensors (e.g., wristbands) have been extensively applied with machine-learning models in construction fields as a means of continuous and less-invasive psychophysiological monitoring. However, there is a significant knowledge gap in how to validate machine-learning models that monitor human responses from biosignals. Specifically, despite the importance of generalizability across different people and contexts for psychophysiological monitoring tasks, current validation methods do not ensure different subjects and contexts between training and testing data sets, and thus overestimate the generalization performance of models. To address this issue, the authors propose a new independent subject and context testing method, leave-one-subject-and-context-out cross validation (LOSCOCV), which ensures that training and testing data sets are collected from different subjects and contexts. The proposed LOSCOCV method’s generalizability estimation performance was compared with current validation methods through conducting a test wherein machine-learning models were developed to detect construction workers’ stress levels from biosignals collected during their ongoing work. The proposed LOSCOCV method showed statistically lower errors in estimating machine-learning models’ generalizability than other benchmarks. The results indicate that LOSCOCV is more valid than current validation methods in assessing models’ generalizability for tasks that monitor human responses from biosignals. Accurately tracking generalization performance is fundamental to efforts toward advancing the generalizability of models. This study therefore significantly contributes to the field’s use of biosensors and machine learning to monitor construction workers’ psychophysiological responses—ultimately advancing their health and safety.
Liu, D, Hu, C, Guo, S and Yu, J (2022) . Journal of Construction Engineering and Management, 148(09).
Liu, J, Liu, J and Bu, Z (2022) Effects of Different Face-Saving Concerns on the Escalation of Commitment between State-Owned and Private Investors in PPP Projects. Journal of Construction Engineering and Management, 148(09).
Liu, M, Zhu, Y, Wei, J, Le, Y and Zhang, X (2022) Impact of Institutional Pressures on External Program Manager Involvement: Evidence from Large Projects in China. Journal of Construction Engineering and Management, 148(09).
Luo, L, Wu, X, Hong, J and Wu, G (2022) Fuzzy Cognitive Map-Enabled Approach for Investigating the Relationship between Influencing Factors and Prefabricated Building Cost Considering Dynamic Interactions. Journal of Construction Engineering and Management, 148(09).
Meng, Q and Zhu, S (2022) Construction Activity Classification Based on Vibration Monitoring Data: A Supervised Deep-Learning Approach with Time Series RandAugment. Journal of Construction Engineering and Management, 148(09).
Naji, K K, Gunduz, M and Naser, A F (2022) The Effect of Change-Order Management Factors on Construction Project Success: A Structural Equation Modeling Approach. Journal of Construction Engineering and Management, 148(09).
Okudan, O and Çevikbaş, M (2022) Alternative Dispute Resolution Selection Framework to Settle Disputes in Public–Private Partnership Projects. Journal of Construction Engineering and Management, 148(09).
Pan, M, Yang, Y, Zheng, Z and Pan, W (2022) Artificial Intelligence and Robotics for Prefabricated and Modular Construction: A Systematic Literature Review. Journal of Construction Engineering and Management, 148(09).
Qiao, J, Wang, C, Guan, S and Shuran, L (2022) Construction-Accident Narrative Classification Using Shallow and Deep Learning. Journal of Construction Engineering and Management, 148(09).
Tang, L, Chen, C, Li, H and Mak, D Y Y (2022) Developing a BIM GIS–Integrated Method for Urban Underground Piping Management in China: A Case Study. Journal of Construction Engineering and Management, 148(09).
Tavallaei, R, Mashayekhi, A, Harrison, N, Talebian, M and Moser, R (2022) BIM Adoption: A Case of Institutional Pressures and Top Management Support. Journal of Construction Engineering and Management, 148(09).
Tayebi Jebeli, M, Asadollahfardi, G and Abbasi Khalil, A (2022) Novel Application of Micro-Nanobubble Water for Recycling Waste Foundry Sand: Toward Green Concrete. Journal of Construction Engineering and Management, 148(09).
ter Huurne, R, Scholtenhuis, L O and Dorée, A (2022) Change Triggers in Early Innovation Stages: How Technology Pilots Enable Routine Reflection. Journal of Construction Engineering and Management, 148(09).
Tian, D, Liu, H, Chen, S, Li, M and Liu, C (2022) Human Error Analysis for Hydraulic Engineering: Comprehensive System to Reveal Accident Evolution Process with Text Knowledge. Journal of Construction Engineering and Management, 148(09).
Xu, Z, Liang, Y, Xu, Y, Fang, Z and Stilla, U (2022) Geometric Modeling and Surface-Quality Inspection of Prefabricated Concrete Components Using Sliced Point Clouds. Journal of Construction Engineering and Management, 148(09).
Yu, W, Wang, K and Wu, H (2022) Empirical Comparison of Learning Effectiveness of Immersive Virtual Reality–Based Safety Training for Novice and Experienced Construction Workers. Journal of Construction Engineering and Management, 148(09).
Zhang, J, Zhou, Q, Li, F and Zhang, S (2022) Case Study of Field Application of Prefabricated Anchoring Frame Beam Structure in Slope Supporting Projects. Journal of Construction Engineering and Management, 148(09).
Zhang, S, Bogus, S M, Lippitt, C D, Kamat, V and Lee, S (2022) Implementing Remote-Sensing Methodologies for Construction Research: An Unoccupied Airborne System Perspective. Journal of Construction Engineering and Management, 148(09).
Zhang, W, Yuan, G, Xue, R, Han, Y and Taylor, J E (2022) Mitigating Common Method Bias in Construction Engineering and Management Research. Journal of Construction Engineering and Management, 148(09).