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    Inherent Feature Connection (I-Con) Map for Liking Emotion Detection: an EEG Study

    HCI 2018

    Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI 2018)

    Belfast, UK, 4 - 6 July 2018


    Zhen Liang, Shigeyuki Oba & Shin Ishii



    Achieving a good recognition and simulation of human emotion is becoming a hot topic in recent years. In this study, we exploited this problem in the liking emotion detection through EEG analysis. To improve the discriminant power of the extracted EEG features, a novel concept of inherent feature connection (I-Con) map was proposed, in which feature-based active channels were estimated and the hidden connections of channels in terms of features were uncovered. This method provided us an efficient and effective way to characterize EEG signals in a better way to reflect the emotion changes in the liking dimension. The performance of the proposed method was demonstrated on a well-known public emotion database.


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