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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Autors principals:	Prabal Datta Barua, Ilknur Tuncer, Emrah Aydemir, Oliver Faust, Subrata Chakraborty, Vinithasree Subbhuraam, Turker Tuncer, Sengul Dogan, U. Rajendra Acharya
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2022-10-01
Col·lecció:	Diagnostics
Matèries:	L-tetrolet pattern sleep stage expert system multiple pooling decomposition insomnia EEG signal classification
Accés en línia:	https://www.mdpi.com/2075-4418/12/10/2510
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