Deep learning-based sleep stage classification with cardiorespiratory and body movement activities in individuals with suspected sleep disorders

Deep learning-based sleep stage classification with cardiorespiratory and body movement activities in individuals with suspected sleep disorders

Abstract Deep learning methods have gained significant attention in sleep science. This study aimed to assess the performance of a deep learning-based sleep stage classification model constructed using fewer physiological parameters derived from cardiorespiratory and body movement data. Overnight po...

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Bibliographic Details
Main Authors: Seiichi Morokuma, Toshinari Hayashi, Masatomo Kanegae, Yoshihiko Mizukami, Shinji Asano, Ichiro Kimura, Yuji Tateizumi, Hitoshi Ueno, Subaru Ikeda, Kyuichi Niizeki
Format: Article
Language:English
Published: Nature Portfolio 2023-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-45020-7

Internet

https://doi.org/10.1038/s41598-023-45020-7

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