Exoskeletons, also known as wearable robots, are being studied as a potential solution to reduce the risk of work-related musculoskeletal disorders (WMSDs) in construction. The exoskeletons can help enhance workers’ postures and provide lift support, reducing the muscular demands on workers while executing construction tasks. Despite the potential of exoskeletons inreducing the risk of WMSDs, there is a lack of understanding about the potential effects ofexoskeletons on workers’ psychological states. This lack of knowledge raises concerns thatexoskeletons may lead to psychological risks, such as cognitive overload, among workers. Tobridge this gap, this study aims to assess the impact of back-support exoskeletons (BSE) onworkers’ cognitive load during material lifting tasks. To accomplish this, a physiologically basedcognitive load assessment framework was developed. This framework used wearable biosensorsto capture the physiological signals of workers and applied Autoencoder and Ensemble Learningtechniques to train a machine learning classifier based on the signals to estimate cognitive loadlevels of workers while wearing the exoskeleton. Results showed that using BSE increasedworkers’ cognitive load by 33% compared to not using it during material handling tasks. Thefindings can aid in the design and implementation of exoskeletons in the construction industry.
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Effect of Time Pressure and Cognitive Demand on Line Workers’ Risk-Taking Behaviors: Assessment of Neuro-Psychophysiological Responses in a Mixed-Reality Environment
Recent research suggests construction workers fall prey to the cognitive biases of risk compensation, wherein workers offset safety improvements by taking more risks. Parallel previous literature indicates that time pressure and mental load may increase workers’ arousal and stress. However, it is unclear whether time, productivity, and/or cognitive demands can worsen risk compensation behaviors by stimulating workers to make riskier decisions to complete tasks faster. Combining a multi-modal mixed-reality environment with wearable neuro-psychophysiological sensors, this study examines changes in safety and task performance for high-risk electrical-line tasks simulated under time/performance pressure and cognitive demand. The results show risk-compensation is in play as subjects over-rely on safety technologies and maintain their risk perception even while undertaking more risks to adapt to increased time pressure and/or cognitive demand. This paper contributes to body of knowledge by affecting safety-training approaches and the controls needed when providing workers with safety protection and new technological advances.
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- Award ID(s):
- 2049711
- NSF-PAR ID:
- 10392308
- Date Published:
- Journal Name:
- Construction Research Congress 2022
- Page Range / eLocation ID:
- 759 to 769
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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One of the main contributors to the human errors that lead to catastrophic injuries in the construction workplace is the failure to identify hazards as a result of poor attention or cognitive lapses. To address this safety concern, the present study used eye-tracking technology to assess how the association between work experience and hazard identification may be mediated due to inattention. A mediation analysis was conducted and tested using a bias-corrected bootstrapping technique with 5000 resamples. The results estimate the direct and indirect effects of work experience on the hazard identification skills of construction workers observing varying hazardous conditions. The results of the mediation analysis confirm that inattention—demonstrated via inattentiveness toward hazards—mediates the relationship between work experience and hazard identification. Specifically, though work experience and dwell time positively correlate with hazard identification, the direct effect of work experience on hazard identification is attenuated with the inclusion of the mediator variables in the model, thus suggesting attentional impairment offsets the benefits of work experience. The outcomes of this study will enable researchers and safety practitioners to harness real-time eye-movement patterns to identify the precursors of cognitive failure, deficient attentional allocation, and poor visual search strategies, all of which may put workers at risk on construction sites. The results also facilitate the provision of personalized safety feedback to workers and the design of training interventions that will address unique performance deficiencies in workers to prevent the human errors that cause injuries in dynamic environments.more » « less
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1061/9780784483985.077
