We present a study on stress detection in virtual reality using The Last Secret, a stealth game we developed that integrates advanced multimodal stress detection techniques and in-game behavioral metrics. Our game responds to the player’s emotional state and stress levels, dynamically adapting its gameplay in real-time. Players need to manage their stress to navigate the game effectively: maintaining calmness keeps them in an optimal flow state, whereas excessive stress can push them into a frustrating state, making progression significantly more difficult. We present experimental results showing the impact of stress-modulated gameplay on player engagement and performance, revealing findings aligned with the flow theory.

A Study on Real-Time Stress Detection in Virtual Reality Using a Stealth Game / S. Brambilla, S. Heidary Moghadam, L.A. Ripamonti, P. Luca Lanzi - In: 2025 IEEE Conference on Games (CoG)[s.l] : Institute of Electrical and Electronics Engineers (IEEE), 2025 Aug. - ISBN 979-8-3315-8905-9. - pp. 1-8 (( convegno IEEE Conference on Games (IEEE CoG) tenutosi a Lisbon nel 2025 [10.1109/CoG64752.2025.11114308].

A Study on Real-Time Stress Detection in Virtual Reality Using a Stealth Game

S. Brambilla;L.A. Ripamonti;
2025

Abstract

We present a study on stress detection in virtual reality using The Last Secret, a stealth game we developed that integrates advanced multimodal stress detection techniques and in-game behavioral metrics. Our game responds to the player’s emotional state and stress levels, dynamically adapting its gameplay in real-time. Players need to manage their stress to navigate the game effectively: maintaining calmness keeps them in an optimal flow state, whereas excessive stress can push them into a frustrating state, making progression significantly more difficult. We present experimental results showing the impact of stress-modulated gameplay on player engagement and performance, revealing findings aligned with the flow theory.
Virtual Reality; Emotion Detection; Stress Detection; Kalman Filter
Settore INFO-01/A - Informatica
ago-2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1171596
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