• DINI HANDAYANI Computer Science Department, Faculty of Information and Communication Technology International Islamic University Malaysia, Malaysia
  • ABDUL WAHAB Computer Science Department, Faculty of Information and Communication Technology International Islamic University Malaysia, Malaysia
  • HAMWIRA YAACOB Computer Science Department, Faculty of Information and Communication Technology International Islamic University Malaysia, Malaysia


Affective computing, mood, emotion recognition, video clip, EEG


This paper presents a subject-dependent homogenous emotion recognition method using electroencephalogram (EEG) signals in response to video contents, and a correlation between emotions and moods of subjects in resting state. In the recent years, there has been a trend towards recognizing emotions invoked from watching videos. Thus, in this study, two video clips with explicit emotional contents from movies and online resources were used, and the EEG results were recorded from four subjects as they watched these clips. The best accuracies of 60.71% for valence and 63.73% for arousal were obtained using a Mel-frequency cepstral coefficients (MFCC) and multilayer perceptron (MLP). The results show that MFCC and MLP techniques are applicable in emotion recognition. The result shows that the mood can be recognized from opened eyes or closed eyes experiment of a subject. Furthermore, the results demonstrated that a positive video content can stimulate a subject into being in positive emotional state even when the subject was in bad mood. The emotional state in response to watching a video was shown to be correlated with Self-Assessment Manikin analysis.



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