Ozdemir, Merve ErkmayYildirim, EsenYildirim, Serdar2024-09-182024-09-182015978-1-4673-7386-92165-0608https://hdl.handle.net/20.500.12483/968323nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYEmotions 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.trinfo:eu-repo/semantics/closedAccessEEGValenceEmotion Primitive ClassificationArtificial Neural NetworksConference Object254925522-s2.0-84939169453N/AWOS:000380500900621N/A