A Shallow Autoencoder Framework for Epileptic Seizure Detection in EEG Signals

This paper presents a trainable hybrid approach involving a shallow autoencoder (AE) and a conventional classifier for epileptic seizure detection. The signal segments of a channel of electroencephalogram (EEG) (EEG epochs) are classified as epileptic and non-epileptic by employing its encoded AE re...

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Detalles Bibliográficos
Autores principales: Khan, Gul Hameed, Khan, Nadeem Ahmad, Altaf, Muhammad Awais Bin, Abbasi, Qammer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10144298/
https://www.ncbi.nlm.nih.gov/pubmed/37112452
http://dx.doi.org/10.3390/s23084112

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10144298/
https://www.ncbi.nlm.nih.gov/pubmed/37112452
http://dx.doi.org/10.3390/s23084112

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