Time–Frequency Statistical Features of Delta Band for Detection of Epileptic Seizures
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-021-08909-y.pdf
Reference18 articles.
1. Trinka, E., Kwan, P., Lee, B. I., & Dash, A. (2019). Epilepsy in Asia: Disease burden, management barriers, and challenges. Epilepsia. https://doi.org/10.1111/epi.14458
2. Teplan, M. (2002). Fundamentals of EEG measurement. Measurement Science Review.
3. Bou Assi, E., Nguyen, D. K., Rihana, S., & Sawan, M. (2017). Towards accurate prediction of epileptic seizures: A review. Biomedical Signal Processing and Control, 34, 144–157. https://doi.org/10.1016/j.bspc.2017.02.001
4. Siddiqui, M. K., Morales-Menendez, R., Huang, X., & Hussain, N. (2020). A review of epileptic seizure detection using machine learning classifiers. Brain Informatics, 7(1), 5. https://doi.org/10.1186/s40708-020-00105-1
5. Boonyakitanont, P., Lek-uthai, A., Chomtho, K., & Songsiri, J. (2020). A review of feature extraction and performance evaluation in epileptic seizure detection using EEG. Biomedical Signal Processing and Control, 57, 101702. https://doi.org/10.1016/j.bspc.2019.101702
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