Emotion recognition by analysis of EEG signals
13th International conference on hybrid intelligent systems (HIS 2013), 2013•ieeexplore.ieee.org
We propose in this paper an emotional recognition system based on physiological signals.
We adopt the seven basic emotions that are: neutrality, joy, sadness, fear, anger, disgust
and surprise. An experiment has been conducted to verify the feasibility of the proposed
system. This experience has allowed us to acquire EEG signals and to create an emotional
database. For this, we have used the Emotiv EPOC headset. Thereafter, we have chosen the
fuzzy logic techniques to classify the EEG signals and to analyze the results.
We adopt the seven basic emotions that are: neutrality, joy, sadness, fear, anger, disgust
and surprise. An experiment has been conducted to verify the feasibility of the proposed
system. This experience has allowed us to acquire EEG signals and to create an emotional
database. For this, we have used the Emotiv EPOC headset. Thereafter, we have chosen the
fuzzy logic techniques to classify the EEG signals and to analyze the results.
We propose in this paper an emotional recognition system based on physiological signals. We adopt the seven basic emotions that are: neutrality, joy, sadness, fear, anger, disgust and surprise. An experiment has been conducted to verify the feasibility of the proposed system. This experience has allowed us to acquire EEG signals and to create an emotional database. For this, we have used the Emotiv EPOC headset. Thereafter, we have chosen the fuzzy logic techniques to classify the EEG signals and to analyze the results.
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