EEG-based Engagement Index for Video Game Players

Abstract

Modern era has changed the lifestyle of the people with technological advancement. Video games have become an integral part of daily entertainment for society. This study proposes an engagement index for a video game using electroencephalography (EEG) and compares its result with existing indices available in the literature. This study employs the use of a 14-channel Emotiv EPOC headset for evaluating the engagement of the players in a video game. The study utilizes the dataset of 10 volunteer participants available on Kaggle. Previously available engagement index calculation techniques utilized three or more features while we propose the use of only two features i.e., theta AF3 and alpha P7 for the calculation of the player's engagement index. Results depict that our proposed index is statistically similar to previous indices, while it needs only two electrodes to gauge player engagement. Additionally, these indices can also differentiate between an expert and a novice player. Thus, it is a step towards the improvement of player experience using dynamic difficulty adjustment (DDA).