Integrating Physiological Responses with Emotion Models: Mapping Emotions in Valence-Arousal Space

In recent years, technologies for recognizing human emotions have gained increasing importance across various fields. Emotions are dynamic cognitive and physiological states that arise as responses to inputs such as experiences, thoughts, and social interactions. A considerable amount of research has been conducted to elucidate the nature of emotions, and several emotion models have been proposed as frameworks for understanding emotions by expressing them in quantitative forms. However, existing emotion models have been constructed based on subjective evaluations and cognitive theories, and therefore, they only capture the cognitive aspects of emotions while failing to reflect their physiological aspects. To address this limitation, it is necessary to construct a novel emotion model that considers both the cognitive and physiological aspects of human emotions. To achieve this construction, it is important to integrate existing emotion models with physiological responses elicited during emotion induction. However, methods for integrating existing emotion models with physiological responses have not been established, and discussions regarding the characteristics of emotions in existing models, considering physiological responses, remain insufficient. Therefore, this study conducted an analysis to clarify the characteristics of emotions in existing models using physiological responses. Specifically, we mapped emotions into Valence-Arousal space using physiological indices during emotion induction and analyzed the spatial distribution characteristics of emotions within the physiological Valence-Arousal space. This study provides new insights for emotion modeling aimed at a deeper understanding of the nature of emotion.