An EEG-Based Brain-Computer Interface for Emotion Recognition

In this paper, an EEG-based brain-computer interface (BCI) system used for emotion recognition is proposed to detect two basic emotional states (happiness and sadness). Selection of frequency bands plays a vital role in distinguishing brain patterns associated with emotions. This paper explores a new method to select suitable subject-specific frequency bands instead of using fixed frequency bands for the emotion recognition. Common spatial pattern and support vector machine were employed to classify two emotional states. Two experiments involving six subjects were conducted to validate our method and BCI system. An average online accuracy of 74.17% for two classes was achieved. The data analysis results demonstrated that the proposed method based on subject-specific frequency bands outperformed the method based on the fixed frequency bands in terms of accuracy.