EEG-Based Emotion Recognition Using Different Neural Network and Pattern Recognition Techniques – A Review - Rajput, Y.M; Hannan, S. Abdul; Eid Alzahrani, M; Manza, Ramesh R; Patil, Dnyaneshwari D (International Journal of Computer Sciences and Engineering, 2019)
Emotion recognition is a critical problem in Human-Computer Interaction. Numerous techniques were useful to enhance the strength of the emotion recognition systems using electroencephalogram (EEG) signals particularly the problem of spatiotemporal features. Automatic emotion recognition founded on EEG signals has received increasing attention in current years. The human being is blessed inquisitiveness has always wondered how to make machines feel, and, at the same time how a machine can detect emotions. In this paper, we elaborated the difference emotion recognition techniques. An automatic approach to address the emotion recognition problem of EEG signals using fused ResNet-50 and LFCC features and several classifiers. Performance of proposed approach with 10fold cross validation and LOO cross validation. Results show that the model is effective for emotion classification. KNN achieves the best performance in dissimilar classifiers.