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© 2022 IEEE.Brain computer interfaces are generally designed for patients with severe disabilities such as motor impairments, but there are also many applications for healthy users. In this study, an Electroencephalogram (EEG) based video game is developed. Although the game is controlled by keyboard, the affective states of the player are predicted using brain signals, and the game difficulty is arranged accordingly. The valence and arousal predictions were tested in an offline analysis, which yielded 0.72 and 0.85 accuracy for valence and arousal levels respectively. The implemented dynamic difficulty adjustment system making use of the valence and arousal levels predicted in real time performed well enough to change the game difficulty to an enjoyable level. |
