A remote and personalised novel approach for monitoring asthma severity levels from EEG signals utilizing classification algorithms

•EEG signals were used for the identification of asthma severity levels.•Three methodologies were designed to identify a subject’s asthma severity levels.•Identifications were made based on subject’s data, new subject’s data, and mixed data.•In two of the methodologies, the ensemble and XGBoost outp...

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Bibliographic Details

Published in:	Expert systems with applications Vol. 223; p. 119799
Main Authors:	Haba, Rotem, Singer, Gonen, Naftali, Sara, Kramer, Mordechai R., Ratnovsky, Anat
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.08.2023
Subjects:	Asthma Electroencephalogram Ensemble learning Machine learning Ordinal classification Electroencephalogram Ensemble learning Ordinal classification Machine learning Asthma
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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