An analysis of engagement levels while playing brain-controlled games

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Abstract

This paper presents a brain-controlled game that allows players to fly a virtual drone using their brain-waves, while the game measures their engagement levels using a BCI. The active BCI element in the game allows players to accelerate and decelerate the virtual drone by performing a motor imagery task (imagining a muscle movement). The passive BCI element processes the EEG signal from the players’ frontal lobe to calculate their engagement in the game. Optionally, the player can see their engagement level as a feedback in the game. This study aims to evaluate (1) the correlation between players’ engagement and performance in brain-controlled games, (2) users’ perception towards receiving feedback on their engagement levels, and (3) the impact of providing engagement level feedback on players’ engagement and performance. A within-subject study with 10 participants was conducted to explore such research questions. Results demonstrate a strong correlation between engagement and performance, measured by the time it took participants to complete each lap in the game. Higher engagement levels resulted in significantly better performance, while low engagement levels led to significantly worse performance. Additionally, qualitative data collected from participants demonstrate a positive attitude towards using engagement level feedback to improve their attention during gameplay.

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APA

Tezza, D., Caprio, D., Pinto, B., Mantilla, I., & Andujar, M. (2020). An analysis of engagement levels while playing brain-controlled games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12211 LNCS, pp. 361–372). Springer. https://doi.org/10.1007/978-3-030-50164-8_26

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