EEG-based emotion recognition using wavelet features


This paper described a research project conducted to recognize to finding the relationship between EEG signals and Human emotions. EEG signals are used to classify three kinds of emotions, positive, neuter and negative. Firstly, literature research has been performed to establish a suitable approach for emotion recognition. Secondly, we extracted features from original EEG data using 4-order wavelet and put them in SVM classifier with different kernel functions. The result shows that an SVM with linear kernel has higher average test accuracy than other kernel function.

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@article{Zhou2014EEGbasedER, title={EEG-based emotion recognition using wavelet features}, author={Zhengjie Zhou and Huiping Jiang and Xiaoyuan Song}, journal={2014 IEEE 5th International Conference on Software Engineering and Service Science}, year={2014}, pages={585-588} }