An approach to arousal disorder classification using deformable convolution and adaptive multiscale features in EEG signals

An approach to arousal disorder classification using deformable convolution and adaptive multiscale features in EEG signals

Diagnosing sleep phases, arousal problems, and apnea episodes using Polysomnography (PSG) signals is often time-consuming. However, automated approaches have demonstrated promising results. Early detection of sleep disturbances can facilitate the diagnosis of neuropathologies before they progress. G...

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Bibliographic Details
Main Authors: Andia Foroughi, Fardad Farokhi, Fereidoun Nowshiravan Rahatabad, Alireza Kashaninia
Format: Article
Language:English
Published: Elsevier 2025-10-01
Series:Brain Research Bulletin
Subjects:
EEG signal
Arousal events
Sleep disorder
Attention module
Hierarchical multiscale deformable
Deformable convolution network
Online Access:http://www.sciencedirect.com/science/article/pii/S0361923025002801
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