Deep convolutional architecture‐based hybrid learning for sleep arousal events detection through single‐lead EEG signals

INTRODUCTION: Detecting arousal events during sleep is a challenging, time‐consuming, and costly process that requires neurology knowledge. Even though similar automated systems detect sleep stages exclusively, early detection of sleep events can assist in identifying neuropathology progression. MET...

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Detalles Bibliográficos
Autores principales: Foroughi, Andia, Farokhi, Fardad, Rahatabad, Fereidoun Nowshiravan, Kashaninia, Alireza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275555/
https://www.ncbi.nlm.nih.gov/pubmed/37199053
http://dx.doi.org/10.1002/brb3.3028

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10275555/
https://www.ncbi.nlm.nih.gov/pubmed/37199053
http://dx.doi.org/10.1002/brb3.3028

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