EEG based emotion recognition using fusion feature extraction method
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EEG based emotion recognition using fusion feature extraction method Qiang Gao 1 & Chu-han Wang 1 & Zhe Wang 1 & Xiao-lin Song 2 & En-zeng Dong 1 & Yu Song 1 Received: 15 October 2019 / Revised: 30 June 2020 / Accepted: 13 July 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
As a high-level function of the human brain, emotion is the external manifestation of people’s psychological characteristics. The emotion has a great impact on people’s personality and mental health. At the same time, emotion classification from electroencephalogram (EEG) signals have attracted much attention. To improve the precision of EEG-based emotion recognition, we proposed a fused feature extraction method to complete the classification of three emotions (neutral, happiness, and sadness). The standardized movie clips were selected to induce the corresponding emotion and the EEG response of 10 participants is collected by Emotiv EPOC. This paper systematically compared two kinds of EEG features (power spectrum and wavelet energy entropy) and their fusion for emotion classification. To reduce the dimension of fused features, we used principal component analysis (PCA) for dimensionality reduction and feature selection. The support vector machine (SVM) classifier and the relevance vector machines (RVM) classifier were utilized for emotion recognition respectively. From experimental results, we found that the fusion of two kinds of features outperformed a single feature for emotion classification by both the SVM classifier and the RVM classifier, and the averaged classification accuracy was 89.17% and 91.18%, respectively. Keywords Power spectrum feature . Wavelet energy entropy feature . Fusion feature . EEG . Emotion recognition
* Yu Song [email protected] Zhe Wang [email protected]
1
Tianjin Key Laboratory for Control Theory and Application in Complicated Systems, Tianjin, China
2
Training Center of Tianjin University of Technology, Tianjin, China
Multimedia Tools and Applications
1 Introduction Emotion is a comprehensive psychological and physiological state produced by various feelings, thoughts, and behaviors, and an external manifestation of some human psychological behaviors. Through the analysis and utilization of emotions, we can peep into the psychological activities of some autistic or depressive patients, or provide psychological counseling to traumatized people to relieve their psychological pressure. Emotion is not only conducive to interpersonal language and emotional communication but also plays an important role in the field of artificial intelligence and human-computer interaction (HCI). It is an interdisciplinary research field covering computer science, artificial intelligence, psychology, medicine, and other disciplines [13]. To represent emotions, the discrete models and dimensional models were proposed by psychologists. A basic emotion theory is represented by Ekman [10], which holds that human emotions are separate, including basic positive emotions such as intere
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