Abstract
High arousal states, like fear and anxiety, play a crucial role in organisms’ adaptive responses to threats. Yet, inducing and reliably measuring such states within controlled settings presents challenges. This study uses a novel approach of CO enriched air vs normal air in a Virtual Reality (VR) context to induce high arousal whilst measuring physiological signals such as galvanic skin response (GSR), facial skin impedance, facial electromyography (fEMG), photoplethysmography (PPG), breathing, and pupillometry. In a single-blind study, 63 participants underwent a regimen involving 20 min of breathing regular air followed by 20 min of 7.5% CO, separated by a brief interval. Findings demonstrate the efficacy of CO inhalation in eliciting high arousal, as substantiated by statistically significant changes for all signals, further validated through high (94%) accuracy arousal classification. This study establishes a method for inducing high arousal states within a laboratory context validated through comprehensive multi-sensor data and machine learning analyses. The study underscores the value of employing a suite of physiological measures to comprehensively describe the intricate dynamics of arousal. The generated database is a promising resource for researching physiological markers of arousal, panic, fear, and anxiety, offering insights that can potentially resonate within clinical and therapeutic realms.
| Original language | English |
|---|---|
| Article number | 103643 |
| Number of pages | 17 |
| Journal | Information Fusion |
| Volume | 126, part B |
| DOIs | |
| Publication status | Published - Feb 2026 |
Keywords
- affective computing
- physiological signals
- virtual reality
- methods of data collection
- arousal
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