Electrodermal Insights into Stress Dynamics of AR-Assisted Safety Warnings in Virtual Roadway Work Zone Environments
Fatemeh Banani Ardecani, Omidreza Shoghli

TL;DR
This research investigates how AR-assisted safety warnings influence stress levels in roadway workers using physiological data, highlighting the potential for real-time stress monitoring to improve safety and work conditions.
Contribution
It introduces a novel approach combining AR warnings with electrodermal activity monitoring in a virtual environment to assess stress responses under different work intensities.
Findings
Significant differences in electrodermal activity between light and medium work intensities.
Peak and central tendency EDR metrics are effective indicators of stress levels.
AR warnings impact worker stress, informing safety system improvements.
Abstract
This study examines stress levels in roadway workers utilizing AR-assisted multi-sensory warning systems under varying work intensities. A high-fidelity Virtual Reality environment was used to replicate real-world scenarios, allowing safe exploration of high-risk situations while focusing on the physiological impacts of work conditions. Wearable sensors were used to continuously and non-invasively collect physiological data, including electrodermal activity to monitor stress responses. Analysis of data from 18 participants revealed notable differences in EDR between light- and medium-intensity activities, reflecting variations in autonomic nervous system activity under stress. Also, a feature importance analysis revealed that peak and central tendency metrics of EDR were robust indicators of physiological responses, between light- and medium-intensity activities. The findings emphasize…
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Taxonomy
TopicsRisk and Safety Analysis · Earthquake Detection and Analysis
