Comparative Evaluation of the EEG Performance Metrics and Player Ratings on the Virtual Reality Games

The low-cost electroencephalogram (EEG) devices are widely used by researchers in human-computer interaction, video games, and software systems to evaluate the impact of interaction design on user emotions. However, the performance metrics of emotion states provided by a low-cost EEG device suffer several reliability and accuracy issues, which can mislead the design decisions of the developers. In this research, we combined the EEG device with three virtual reality games to investigate the reliability of performance metrics extracted from the EEG data. We conducted the experiment with 14 players using virtual reality games with ranging levels of in-game actions. Our analysis shows that there is a significant difference between performance metrics provided by the EEG device and the actual players' experience. Finally, we used ad-hoc linear models to estimate the level of players' emotion states directly from the raw EEG. We also show the different brain activity maps for individual emotions, which reveal the commonly known relation between brain activity and specific emotions.