Epileptic Seizure Detection and Prediction for Patient Support
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-67088-6_3
Reference46 articles.
1. Li, Y., Liu, Y., Cui, W.G., Guo, Y.Z., Huang, H., Hu, Z.Y.: Epileptic seizure detection in EEG signals using a unified temporal-spectral squeeze-and-excitation network. IEEE Trans. Neural Syst. Rehabil. Eng. 28(4), 782–794 (2020)
2. Yuan, Y., Xun, G., Jia, K., Zhang, A.: A multi-view deep learning framework for EEG seizure detection. IEEE J. Biomed. Health Inform. 23, 83–94 (2019)
3. Yang, S., et al.: Selection of features for patient-independent detection of seizure events using scalp EEG signals. Comput. Biol. Med. 119 (2020)
4. Jiang, Z., Zhao, W.: Optimal selection of customized features for implementing seizure detection in wearable electroencephalography sensor. IEEE Sens. J. 20(21), 12941–12949 (2020)
5. Khanmohammadi, S., Chou, C.A.: Adaptive seizure onset detection framework using a hybrid PCA-CSP approach. IEEE J. Biomed. Health Inform. 22(1), 154–160 (2018)
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