Quaternary classification of emotions based on electroencephalogram signals using hybrid deep learning model
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-022-04495-4.pdf
Reference46 articles.
1. Acharya D, Goel S, Bhardwaj H, Sakalle A and Bhardwaj A (2020) A long short term memory deep learning network for the classification of negative emotions using eeg signals. In: 2020 international joint conference on neural networks (ijcnn), 1–8. https://doi.org/10.1109/IJCNN48605.2020.9207280
2. Ahirwal MK and Kose MR (2018) Emotion recognition system based on eeg signal: a comparative study of different features and classifiers. In 2018 second international conference on computing methodologies and communication (iccmc), 472–476. https://doi.org/10.1109/ICCMC.2018.8488044
3. Ahirwal MK, Kumar A, Singh GK (2014) A new approach for utilisation of single erp to control multiple commands in bci. Int J Electron Lett 2(3):166–171. https://doi.org/10.1080/21681724.2014.894133
4. Alakus TB, Gonen M, Turkoglu I (2020) Database for an emotion recognition system based on eeg signals and various computer games - gameemo. Biomed Signal Process Control 60:101951
5. AlZoubi O, AlMakhadmeh B, Yassein MB, Mardini W (2021) Detecting naturalistic expression of emotions using physiological signals while playing video games. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-021-03367-7
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