Abstract :
[en] Predicting affective and cognitive states through brain activity can enhance user experience, particularly in adaptive games that need to adjust difficulty according to the user’s mood as gameplay progresses. While previous studies have focused on isolated applications of brain signals, integrating multiple brain-related features
remains a challenge. We present an adaptive Brain-Computer Interface (BCI) game that processes electroencephalogram (EEG) signals in real-time, dynamically adjusting the difficulty and environment of the game based on detected mental fatigue, with blink activity serving as a control mechanism. Our preliminary results demonstrate an effective integration of multimodal biofeedback, providing valuable information on the usability of EEG for adaptive games.
Funding text :
Research supported by the Horizon 2020 FET program of the European Union through the ERA-NET Cofund funding (grant CHIST-ERA-20-BCI-001) and the European Innovation Council Pathfinder program (SYMBIOTIK project, grant 101071147).
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