Abstract
Emotion recognition, as an important part of human-computer interaction, has been extensively researched. Various studies have already verified the relationship between emotion and the event-related potentials (ERPs). In this paper, a new methodology for emotion recognition is investigated by detecting single-trial ERPs related to some specific level of emotions. First, a spatial filter is constructed to estimate the ERP components. Then the most discriminative spatial and temporal features of the entire ERP waveform are extracted with linear discriminant analysis. The performance of this method is tested by classifying the emotional valence on three levels, the extremely negative, the moderately negative and the neutral, with the support vector machine (SVM). The result shows that the proposed method is effective.