Long, Fangfang and Zhao, Shanguang and Wei, Xin and Ng, Siew Cheok and Ni, Xiaoli and Chi, Aiping and Fang, Peng and Zeng, Weigang and Wei, Bokun (2021) Positive and negative emotion classification based on multi-channel. Frontiers In Behavioral Neuroscience, 15. ISSN 1662-5153, DOI https://doi.org/10.3389/fnbeh.2021.720451.
Full text not available from this repository.Abstract
The EEG features of different emotions were extracted based on multi-channel and forehead channels in this study. The EEG signals of 26 subjects were collected by the emotional video evoked method. The results show that the energy ratio and differential entropy of the frequency band can be used to classify positive and negative emotions effectively, and the best effect can be achieved by using an SVM classifier. When only the forehead and forehead signals are used, the highest classification accuracy can reach 66%. When the data of all channels are used, the highest accuracy of the model can reach 82%. After channel selection, the best model of this study can be obtained. The accuracy is more than 86%.
| Item Type: | Article |
|---|---|
| Funders: | Department of Military Medical Psychology, Air Force Medical University, Xian, Major Project of Medicine Science and Technology of PLA (AWS17J012), National Natural Science Foundation of China (NSFC) (61806210), National Natural Science Foundation of China (NSFC) (Xian 710032) |
| Uncontrolled Keywords: | EEG; Emotion classification; Support vector machine; Decision tree; Back propagation neural network; K-nearest neighbor |
| Subjects: | R Medicine |
| Divisions: | Faculty of Engineering > Biomedical Engineering Department Faculty of Sports and Exercise Science (formerly known as Centre for Sports & Exercise Sciences) |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 08 Sep 2022 04:08 |
| Last Modified: | 08 Sep 2022 04:08 |
| URI: | http://eprints.um.edu.my/id/eprint/34221 |
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