Improving the detection of sleep slow oscillations in electroencephalographic data

Improving the detection of sleep slow oscillations in electroencephalographic data

Study objectivesWe aimed to build a tool which facilitates manual labeling of sleep slow oscillations (SOs) and evaluate the performance of traditional sleep SO detection algorithms on such a manually labeled data set. We sought to develop improved methods for SO detection.MethodSOs in polysomnograp...

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Bibliographic Details
Main Authors: Cristiana Dimulescu, Leonhard Donle, Caglar Cakan, Thomas Goerttler, Lilia Khakimova, Julia Ladenbauer, Agnes Flöel, Klaus Obermayer
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Neuroinformatics
Subjects:
electroencephalography
sleep
slow oscillations
event detection
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2024.1338886/full

Internet

https://www.frontiersin.org/articles/10.3389/fninf.2024.1338886/full

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