Key result
An AI-based hybrid classifier using galvanic skin response and photoplethysmogram signals detected anxiety elicited without time pressure with 96.08% accuracy.
Why the study?
Laboratory studies eliciting anxiety have less widely considered inducing anxiety independently of time pressure.
An AI-based classifier using GSR, PPG, and HR signals can accurately detect anxiety elicited without time pressure, achieving over 96% accuracy.
High-accuracy wearable detection of non-temporal anxiety feasible; leaves open larger validation before clinical or research adoption.
Stress can be defined as a state of anxiety (or mental tension) caused by a particular situation. Everybody experiences stress to some level, but how we respond to stress significantly affects our well-being. Various events generate anxiety that leads to stress. For example, not having enough time to complete a task or being late are situations where anxiety (and stress) depends on a temporal factor: the scarcity of time. But people also slide into anxiety as they live in a condition that causes them to be tense, independently of time. The studies eliciting anxiety in laboratory settings have less widely considered this variant. This paper presents a proof of concept (PoC) that investigated the possibility of stimulating anxiety without time pressure through a purposely edited horror movie trailer, giving new insights into the emotional experiences evoked by controlled audiovisual stimuli. The PoC comprised an AI-based classifier to detect a person’s emotion amonganxiety,relaxation, andnone of the twobased on the galvanic skin response (GSR), photoplethysmogram (PPG), and heart rate (HR), achieving an accuracy higher than 96%. Key application areas include media and marketing, and psychology. Media producers could improve their content to capture the audience better; psychologists could create tailored exposure experiences to promote gradual desensitization to stress triggers.
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Tecco et al. (2024) studied Healthy volunteers (Anxiety elicitation) (n=32). Edited horror movie trailer (IT: Chapter One) vs. Relaxing video clip was evaluated on Classification accuracy of the hybrid AI system (S2) in detecting anxiety, relaxation, or another emotion. An AI-based hybrid classifier using galvanic skin response and photoplethysmogram signals detected anxiety elicited without time pressure with 96.08% accuracy.
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