PSG-Based Classification of Sleep Phases
Alternative metrics PlumXhttp://hdl.handle.net/11012/42980
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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.
Document typePeer reviewed
SourceProceedings of the 21st Conference STUDENT EEICT 2015. s. 215-217. ISBN 978-80-214-5148-3
- Student EEICT 2015