A Survey on EEG Based Emotion Analysis Using Various Techniques

Abstract

Emotions play a significant role in human cognition, perception, decision making, and interaction. The main objective of this research methodology is to find, implement and evaluate the various research issues that has been conducted to achieve the high classification rate for Emotion Analysis. Most of the existing system used various pre-processing, feature extraction and classification methods to emotion classification. The classification algorithms like support vector machine, PNN classifier, adaptive neuro-fuzzy inference (ANFIS) classifier, Artificial Neural Network (ANN), Linear discriminant Analysis (LDA), K-Nearest Neighbor (KNN) are used in existing scenarios. In the proposed scenario, Non Negative Principal Component Analysis is used for emotion classification.The performance evaluation conducted were proves that the proposed mechanism gives better result when compared to the existing mechanism in terms of improved accuracy and reduced execution time.