EEG-enabled Affective Human-Computer Interfaces
Nowadays, the human computer interfaces can be designed to be adaptive and emotion-enabled. The recognized emotions of the user can help make the user’s experience more complete, more engaging, less stressful or more stressful depending on the target of the applications. Such affective human-computer interfaces are getting more attention from researchers and engineers. EEG signals are used to recognize emotions of the user in real time. We describe a real-time emotion recognition algorithm that is used to personalize different applications according to the user’s current emotions. The algorithm is subject-dependent and needs a training session before running the application. Two EEG-enabled games and one adaptive advertisement based on the algorithm are designed and implemented. One game is the “Bar” game where a difficulty level of the game is adapted based on the player’s score and emotions. Another game is the “Girl Twins” one where the player’s emotions are monitored in real time, and an emotional companion is implemented as the girl twins avatars whose behaviour changes according to the user’s emotions. An adaptive advertising movie is designed and implemented as well. Here, the real-time emotion recognition algorithm is used to adjust the scenes of the advertisement based on the current emotion recognized.
KeywordsEEG adaptive interfaces emotion recognition BCI affective computing
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