Sleep staging in the ICU with heart rate variability and breathing signals. An exploratory cross-sectional study using deep neural networks

Introduction: To measure sleep in the intensive care unit (ICU), full polysomnography is impractical, while activity monitoring and subjective assessments are severely confounded. However, sleep is an intensely networked state, and reflected in numerous signals. Here, we explore the feasibility of e...

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Detalles Bibliográficos
Autores principales: Ganglberger, Wolfgang, Krishnamurthy, Parimala Velpula, Quadri, Syed A., Tesh, Ryan A., Bucklin, Abigail A., Adra, Noor, Da Silva Cardoso, Madalena, Leone, Michael J., Hemmige, Aashritha, Rajan, Subapriya, Panneerselvam, Ezhil, Paixao, Luis, Higgins, Jasmine, Ayub, Muhammad Abubakar, Shao, Yu-Ping, Coughlin, Brian, Sun, Haoqi, Ye, Elissa M., Cash, Sydney S., Thompson, B. Taylor, Akeju, Oluwaseun, Kuller, David, Thomas, Robert J., Westover, M. Brandon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Network Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013021/
https://www.ncbi.nlm.nih.gov/pubmed/36926545
http://dx.doi.org/10.3389/fnetp.2023.1120390

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013021/
https://www.ncbi.nlm.nih.gov/pubmed/36926545
http://dx.doi.org/10.3389/fnetp.2023.1120390

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