Influence of Channel Selection and Subject’s Age on the Performance of the Single Channel EEG-Based Automatic Sleep Staging Algorithms

The electroencephalogram (EEG) signal is a key parameter used to identify the different sleep stages present in an overnight sleep recording. Sleep staging is crucial in the diagnosis of several sleep disorders; however, the manual annotation of the EEG signal is a costly and time-consuming process....

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Veröffentlicht in:	Sensors (Basel, Switzerland) Jg. 23; H. 2; S. 899
Hauptverfasser:	Nazih, Waleed, Shahin, Mostafa, Eldesouki, Mohamed I., Ahmed, Beena
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland MDPI AG 12.01.2023 MDPI
Schlagworte:	Accuracy Adult Age Algorithms Child Classification Datasets Deep learning EEG electroencephalogram Electroencephalography Electroencephalography - methods Eye movements Humans Infant, Newborn Machine learning Neural networks pediatric Pediatrics Reproducibility of Results Sleep Sleep disorders sleep stage scoring Sleep Stages Support vector machines deep learning sleep stage scoring EEG electroencephalogram pediatric
ISSN:	1424-8220, 1424-8220
Online-Zugang:	Volltext
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