The Magic XRoom: A Flexible VR Platform for Controlled Emotion Elicitation and Recognition
S. M. Hossein Mousavi, Matteo Besenzoni, Davide Andreoletti, Achille, Peternier, Silvia Giordano

TL;DR
The paper introduces the Magic Xroom, a VR platform that uses the theory of flow to control emotion elicitation and collect data for emotion recognition research, addressing challenges in affective computing.
Contribution
It presents a novel VR platform that dynamically adjusts task difficulty based on user skill to evoke specific emotions and facilitates high-quality data collection for emotion recognition.
Findings
Effective emotion elicitation through skill-based task adjustment
Enhanced data collection for emotion recognition research
Demonstrated virtual scenarios illustrating platform capabilities
Abstract
Affective computing has recently gained popularity, especially in the field of human-computer interaction systems, where effectively evoking and detecting emotions is of paramount importance to enhance users experience. However, several issues are hindering progress in the field. In fact, the complexity of emotions makes it difficult to understand their triggers and control their elicitation. Additionally, effective emotion recognition requires analyzing multiple sensor data, such as facial expressions and physiological signals. These factors combined make it hard to collect high-quality datasets that can be used for research purposes (e.g., development of emotion recognition algorithms). Despite these challenges, Virtual Reality (VR) holds promise as a solution. By providing a controlled and immersive environment, VR enables the replication of real-world emotional experiences and…
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