Ozel, PinarAkan, AydinYilmaz, Bulent2021-08-092021-08-092017978-1-5386-1723-6https://hdl.handle.net/20.500.12573/913Recently, there has been a rapid development in multivariate signal analysis to determine joint oscillations for multiple data channels. The emotion elicitation in an electroencephalogram (EEG) is a novel area to evaluate methods for emotional differences from brain signals. In this paper, utilizing the idea of joint instantaneous frequency of multivariate data, a multivariate extension of pseudo Wigner distribution is used for emotion recognition from EEG signals, in which different window sizes are employed to interpret the results. As a preliminary study, the best results are obtained as 90%, 75%, 65% in terms of valence, arousal and dominance scale respectively for larger window size.enginfo:eu-repo/semantics/closedAccessRECOGNITIONMultivariate Pseudo Wigner Ville Distribution based Emotion Detection from Electrical Activity of BrainconferenceObject516519