期刊名称：American Journal of Computing Research Repository
印刷版ISSN：2377-4606
电子版ISSN：2377-4266
出版年度：2014
卷号：2
期号：4
页码：66-70
DOI：10.12691/ajcrr-2-4-3
语种：English
出版社：Science and Education Publishing
摘要：Recently, the field of Brain-Computer interface has gained a great deal of attention. In this work, we present some promising results of our research in classification of emotions induced by watching music videos. More specially, we aim to analyze users' passive physiological responses as they watch video clips. We use DEAP data base for this purpose. We show robust correlations between users’ self-assessments of arousal and valence and the frequency Entropy and powers of their EEG activity. Also we found that high frequency bands give higher accuracy than low frequency bands especially EEG in Gamma band that give accuracy at 73.84% (for valence) and 69.82% (for arousal). EEG signals were decomposed to 5 frequency bands by Continuous Wavelet Transform (CWT) using the 2.8 Biorthogonal wavelet.
