Elicitation of Anxiety Without Time Pressure and Its Detection Using Physiological Signals and Artificial Intelligence: A Proof of Concept

Abstract

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 among anxiety, relaxation, and none of the two based on the galvanic skin response (GSR), photoplethysmogram (PPG), and heart rate (HR), achieving an accuracy higher than 95%. 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.

Keywords

• Affective computing
• anxiety
• artificial intelligence
• galvanic skin response
• heart rate
• pattern recognition