Classification of emotional valence dimension using artificial neural networks

Emotions play an important role in human interaction. Emotion recognition should be considered to design an effective Brain-Computer Interface. In this work binary classification (low/high) for valence which is one of the primitives used in expressing emotions is performed. Hilbert-Huang Transform is used for feature extraction, multi layer feed forward Artificial Neural Networks is used for subject independent classification and 69% of true positive rate is obtained.