L-Tetrolet Pattern-Based Sleep Stage Classification Model Using Balanced EEG Datasets

Background: Sleep stage classification is a crucial process for the diagnosis of sleep or sleep-related diseases. Currently, this process is based on manual electroencephalogram (EEG) analysis, which is resource-intensive and error-prone. Various machine learning models have been recommended to stan...

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Detalles Bibliográficos
Autores principales: Barua, Prabal Datta, Tuncer, Ilknur, Aydemir, Emrah, Faust, Oliver, Chakraborty, Subrata, Subbhuraam, Vinithasree, Tuncer, Turker, Dogan, Sengul, Acharya, U. Rajendra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600064/
https://www.ncbi.nlm.nih.gov/pubmed/36292199
http://dx.doi.org/10.3390/diagnostics12102510

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9600064/
https://www.ncbi.nlm.nih.gov/pubmed/36292199
http://dx.doi.org/10.3390/diagnostics12102510

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