Disclosed is an emotion recognition method based on multivariate multiscale fuzzy entropy analysis of EEG. Among the various physiological signals, the electroencephalography (EEG) signal is an immediate and continuous signal of brain activity, and is mainly used for emotional analysis because it can directly reflect changes in a person's emotional state. Multivariate Fuzzy Entropy (mvFE) and Multivariate Empirical Mode in order to express the entropy of the EEG signals recorded from several EEG electrodes (to quantify the complexity) and to show the characteristics at different time scales. Decomposition, MEMD) was used to analyze the emotional state. EEG data from DEAP, a public database, was used to analyze emotional states, and it was shown that it is possible to distinguish emotional states through binary classification of higher/lower arousal and positiveegative emotions (Valence) than the reference value.
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