CNN models for EEG motor imagery signal classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-022-02293-1.pdf
Reference32 articles.
1. Roy, Y., et al.: Deep learning-based electroencephalography analysis: a systematic review. J. Neural Eng. 16(5), 051001 (2019)
2. Al-Saegh, A., Dawwd, S.A., Abdul-Jabbar, J.M.: Deep learning for motor imagery EEG-based classification: a review. Biomed. Signal Process. Control 63, 102172 (2021)
3. Craik, A., He, Y., Contreras-Vidal, J.L.: Deep learning for electroencephalogram (EEG) classification tasks: a review. J. Neural Eng. 16(3), 031001 (2019)
4. Merlin Praveena, D., Angelin Sarah, D. & Thomas George, S.: Deep learning techniques for EEG signal applications: a review. IETE J. Res. 1–8 (2020)
5. Li, G., Lee, C.H., Jung, J.J., Youn, Y.C., Camacho, D.: Deep learning for EEG data analytics: a survey. Concurr. Comput. Pract. Exp. 32(18), e5199 (2020)
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