PSG-Based Classification of Sleep Phases
Loading...
Date
2015
Authors
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
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.
Description
Citation
Proceedings of the 21st Conference STUDENT EEICT 2015. s. 215-217. ISBN 978-80-214-5148-3
http://www.feec.vutbr.cz/EEICT/
http://www.feec.vutbr.cz/EEICT/
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
cs
Study field
Comittee
Date of acceptance
Defence
Result of defence
Document licence
© Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií