Emotion modeling using Fuzzy Cognitive Maps

In this study, Fuzzy Cognitive Map (FCM) modeling technique on emotion recognition problem with regression of arousal and valence values is applied and Big Bang - Big Crunch learning method is used for developing the model. Emotions play a critical role of humans´ behaviors, beliefs, motivations and decisions. Developing a model between bodily responses and emotional states of a human is an extremely challenging problem in affective computing area. In this study, DEAP dataset, which is publicly available, is used as a dataset. The set contains the recordings of physiological modalities for participant, each participant viewing video clips and reporting emotional states with using self assessment manikins. The results of various simulations show that FCM is a useful and convenient tool for emotion modeling.