Classification of Brainwaves for Sleep Stages by High-Dimensional FFT Features from EEG Signals

Manual classification of sleep stage is a time-consuming but necessary step in the diagnosis and treatment of sleep disorders, and its automation has been an area of active study. The previous works have shown that low dimensional fast Fourier transform (FFT) features and many machine learning algor...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Mera Kartika Delimayanti, Bedy Purnama, Ngoc Giang Nguyen, Mohammad Reza Faisal, Kunti Robiatul Mahmudah, Fatma Indriani, Mamoru Kubo, Kenji Satou
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2020-03-01
coleção:	Applied Sciences
Assuntos:	automatic sleep stage classification electroencephalogram fast fourier transform
Acesso em linha:	https://www.mdpi.com/2076-3417/10/5/1797
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!