A Survey on Assessment of Sentiments and Emotions Using EEG Signals

Abstract

Electroencephalography (EEG) based emotion detection is important for describing the human behavior. EEG is considered more convenient in emotion detection due to the properties of non-stationary, non-linear and high dimensional. Since, the human emotions plays important role in rational decision-making, human intelligence, human interaction and perception.The emotional state of the parameter is divided as two dimensional parameter space called arousal and valence. The detection of human emotion is important in various fields such as artificial intelligence, computer science, psychology, cognitive science and neuroscience.In this paper, the important definitions of EEG signal based emotion detection are described and it carried out the publically EEG datasets for emotion detection. Accordingly, the DEAP is one of the publically available EEG dataset for emotion detection. This paper surveyed the conventional methods utilized for emotion detection through EEG signals along with its limitations. The classification accuracy is one of the important parameter to define the effectiveness of the emotion detection. This comprehensive survey helps the researchers for achieving the better solution for the current concerns faced in emotion classification in EEG signals.