Frontal EEG Asymmetry Based Classification of Emotional Valence using Common Spatial Patterns
In this work we evaluate the possibility of predicting
the emotional state of a person based on the EEG. We investigate
the problem of classifying valence from EEG signals during
the presentation of affective pictures, utilizing the "frontal EEG
asymmetry" phenomenon. To distinguish positive and negative
emotions, we applied the Common Spatial Patterns algorithm.
In contrast to our expectations, the affective pictures did not
reliably elicit changes in frontal asymmetry. The classifying task
thereby becomes very hard as reflected by the poor classifier
performance. We suspect that the masking of the source of the
brain activity related to emotions, coming mostly from deeper
structures in the brain, and the insufficient emotional engagement
are among main reasons why it is difficult to predict the emotional
state of a person.
Emotion, Valence, EEG, Common Spatial Patterns(CSP).