Rules-Based and SVM-Q Methods With Multitapers and Convolution for Sleep EEG Stages Classification

Rules-Based and SVM-Q Methods With Multitapers and Convolution for Sleep EEG Stages Classification

Sleep EEG signals analysis is an approach that helps researchers identify and understand the different phenomena concealed within sleep EEG data. This research introduces a time-frequency analysis approach to untangle the parameters of the sleep stages classification from EEG data. This approach com...

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Bibliographic Details
Main Authors: Ignacio A. Zapata, Yan Li, Peng Wen
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Multitapers
support vector machine
SVM-Q
spectral estimation
sleep EEG
sleep stages
Online Access:https://ieeexplore.ieee.org/document/9815054/

Internet

https://ieeexplore.ieee.org/document/9815054/

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