Assessing workers’ neuro-physiological stress responses to augmented reality safety warnings in immersive virtual roadway work zones

This paper presents a multi-stage experimental framework that integrates immersive Virtual Reality (VR) simulations, wearable sensors, and advanced signal processing to investigate construction workers’ neuro-physiological stress responses to multi-sensory AR-enabled warnings. Participants performed light- and moderate-intensity roadway maintenance tasks within a high-fidelity VR roadway work zone, while key stress markers of electrodermal activity (EDA), heart rate variability (HRV), and electroencephalography (EEG) were continuously measured. Statistical analyses revealed that task intensity significantly influenced physiological and neurological stress indicators. Moderate-intensity tasks elicited greater autonomic arousal, evidenced by elevated heart rate measures (mean-HR, std-HR, max-HR) and stronger electrodermal responses (EDR), while EEG data indicated distinct stress-related alpha suppression and beta enhancement. Feature-importance analysis further identified mean EDR and short-term HR metrics as discriminative for classifying task intensity. Correlation results highlighted a temporal lag between immediate neural changes and subsequent physiological stress reactions, emphasizing the interplay between cognition and autonomic regulation during hazardous tasks. • Assesses AR-based warnings under light vs. moderate tasks in VR work zones. • Tracks HR, HRV, EDR, and EEG to evaluate physiological and cognitive stress. • Identifies EDR and short-term HR as key markers of task intensity. • Discovers time lag between neural changes and physiological stress signals. • Proposes adaptive AR warnings based on real-time stress detection.