Dynamic Difficulty Adjustment With Brain Waves as a Tool for Optimizing Engagement

This study explores the use of electroencephalography (EEG)-based brain wave monitoring to enable dynamic difficulty adjustment (DDA) in a virtual reality (VR) gaming environment. Using the Task Engagement Index (TEI) derived from frontal EEG electrodes, we adapt game challenge levels in real time to maintain optimal player engagement. In a within-subject design with six participants, we found that the DDA condition significantly increased engagement duration by 19.79% compared to a non-DDA control condition. These results suggest that combining EEG, DDA, and VR technologies can enhance user experience and has potential applications in adaptive learning, rehabilitation, and personalized interfaces.

Publication Details

Journal
ArXiv.org
Published
2025-04-17
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
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article

Dynamic Difficulty Adjustment With Brain Waves as a Tool for Optimizing Engagement

ArXiv.org
EEG and Brain-Computer Interfaces
article

Dynamic Difficulty Adjustment With Brain Waves as a Tool for Optimizing Engagement

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Abstract

This study explores the use of electroencephalography (EEG)-based brain wave monitoring to enable dynamic difficulty adjustment (DDA) in a virtual reality (VR) gaming environment. Using the Task Engagement Index (TEI) derived from frontal EEG electrodes, we adapt game challenge levels in real time to maintain optimal player engagement. In a within-subject design with six participants, we found that the DDA condition significantly increased engagement duration by 19.79% compared to a non-DDA control condition. These results suggest that combining EEG, DDA, and VR technologies can enhance user experience and has potential applications in adaptive learning, rehabilitation, and personalized interfaces.

ArXiv.org
Openalex Percentile: Top 47%
EEG and Brain-Computer Interfaces
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