Original title: PSG-Based Classification of Sleep Phases
Authors: Králík, M.
Document type: Papers
Language: cze
Publisher: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií
Abstract: This work is focused on classification of sleep phases using artificial neural network. The unconventional approach was used for calculation of classification features using polysomnographic data (PSG) of real patients. This approach allows to increase the time resolution of the analysis and, thus, to achieve more accurate results of classification.
Keywords: classification features; neural networks; polysomnography; sleep scoring
Host item entry: Proceedings of the 21st Conference STUDENT EEICT 2015, ISBN 978-80-214-5148-3

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/42980

Permalink: http://www.nusl.cz/ntk/nusl-207171


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Universities and colleges > Public universities > Brno University of Technology
Conference materials > Papers