Emotion recognition classification by EEG based on spectrum analysis

抄録

Research shows that human emotion is closely related to the activity correlation of cerebral cortex, so the research of emotion classification by EEG (Electroencephalogram) provides a reliable basis. The feature extraction and classification application for EEG has been greatly improved in recent years, so we use EEG to study emotion classification. However, there are differences between EEG signals of different subjects, which have a certain impact on emotion classification. How to ensure the high accuracy and robustness of recognition is a problem. For this problem, when studying different subjects in different states, spectrum analysis can be used for their feature extraction. When the extracted features are classified, discriminant analysis algorithm is used and achieved better classification results. There are many methods involved in feature extraction, and different feature extraction methods will be compared later, so as to improve the robustness and efficiency of emotional classification by EEG signals.