Impact of Feature Selection Techniques for EEG-Based Seizure Classification
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-9379-4_16
Reference25 articles.
1. Hussein R, Ahmed MO, Ward R, Wang ZJ, Kuhlmann L, Guo Y (2019) Human intracranial EEG quantitative analysis and automatic feature learning for epileptic seizure prediction. arXiv preprint arXiv:1904.03603. https://doi.org/10.48550/arXiv.1904.03603
2. Yang S, Li B, Zhang Y, Duan M, Liu S, Zhang Y, Feng X, Tan R, Huang L, Zhou F (2020) Selection of features for patient-independent detection of seizure events using scalp EEG signals. Comput Biol Med 119:103671. https://doi.org/10.1016/j.compbiomed.2020.103671
3. Singh A, Trevick S (2016) The epidemiology of global epilepsy. Neurol Clin 34(4):837–847. https://doi.org/10.1016/j.ncl.2016.06.015
4. Farahmand S, Sobayo T, Mogul DJ (2018) Noise-assisted multivariate EMD-based mean-phase coherence analysis to evaluate phase-synchrony dynamics in epilepsy patients. IEEE Trans Neural Syst Rehabil Eng 26(12):2270–2279. https://doi.org/10.1109/TNSRE.2018.2881606
5. Fisher RS, Boas WV, Blume W, Elger C, Genton P, Lee P, Engel J Jr (2005) Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE). Epilepsia 46(4):470–472. https://doi.org/10.1111/j.0013-9580.2005.66104.x
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