A Comparative Analysis of Machine and Deep Learning Techniques for EEG Evoked Emotion Classification-Reference-Cited by-同舟云学术

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A Comparative Analysis of Machine and Deep Learning Techniques for EEG Evoked Emotion Classification

Published:2022-10-14 Issue:4 Volume:128 Page:2869-2890
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Kumari Nandini,Anwar Shamama,Bhattacharjee Vandana

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

https://link.springer.com/content/pdf/10.1007/s11277-022-10076-7.pdf

Reference49 articles.

1. Cheng, J., Chen, M., Li, C., Liu, Y., Song, R., Liu, A., & Chen, X. (2020). Emotion recognition from multi-channel EEG via deep forest. IEEE Journal of Biomedical and Health Informatics, 25(2), 453–464.

2. Liu, Yu., Ding, Y., Li, C., Cheng, J., Song, R., Wan, F., & Chen, X. (2020). Multi-channel EEG-based emotion recognition via a multi-level features guided capsule network. Computers in Biology and Medicine, 123, 103927.

3. Ali, Mouhannad., Mosa, Ahmad Haj., Machot, Fadi Al., & Kyamakya, Kyandoghere. (2016) EEG-based emotion recognition approach for e-healthcare applications. In 2016 eighth international conference on ubiquitous and future networks (ICUFN), pages 946–950. IEEE,

4. Tao, W., Li, C., Song, R., Cheng, J., Liu, Y., Wan, F., & Chen, X. (2020) EEG-based emotion recognition via channel-wise attention and self attention. IEEE Transactions on Affective Computing, 1–12. https://doi.org/10.1109/TAFFC.2020.3025777

5. Jenke, R., Peer, A., & Buss, M. (2014). Feature extraction and selection for emotion recognition from EEG. IEESE Transactions on Affective computing, 5(3), 327–339.

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