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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Autors principals:	Cristiana Dimulescu, Leonhard Donle, Caglar Cakan, Thomas Goerttler, Lilia Khakimova, Julia Ladenbauer, Agnes Flöel, Klaus Obermayer
Format:	Artigo
Idioma:	Inglês
Publicat:	Frontiers Media S.A. 2024-02-01
Col·lecció:	Frontiers in Neuroinformatics
Matèries:	electroencephalography sleep slow oscillations event detection deep learning
Accés en línia:	https://www.frontiersin.org/articles/10.3389/fninf.2024.1338886/full
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