A convolutional neural network to classify sleep stages in pediatric sleep apnea from pulse oximetry signals-Reference-Cited by-同舟云学术

A convolutional neural network to classify sleep stages in pediatric sleep apnea from pulse oximetry signals

Published:2022-06-14 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON)
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Author:

Vaquerizo-Villar Fernando¹,Alvarez Daniel¹,Gutierrez-Tobal Gonzalo C.¹,Campo Felix Del²,Kheirandish-Gozal Leila³,Gozal David³,Penzel Thomas⁴,Hornero Roberto¹

Affiliation:

1. Universidad de Valladolid, Centro de Investigatión Biomédica en Red en Bioingeniería Biomateriales y Nanomedicina, (CIBER-BBN),Biomedical Engineering Group,Valladolid,Spain

2. Hospital Universitario Río Hortega,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN),Valladolid,Spain

3. The University of Missouri School of Medicine,Department of Child Health,Columbia,Missouri,USA

4. Charité-Universitätsmedizin Berlin,Interdisciplinary Center of Sleep Medicine,Berlin,Germany

Funder

Ministerio de Ciencia e Innovación

Sociedad Española de Neumología y Cirugía Torácica

European Social Fund

Sears

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9842860/9842863/09842917.pdf?arnumber=9842917

Reference23 articles.

1. Sleep apnea: a review of diagnostic sensors, algorithms, and therapies

2. Reliability of machine learning to diagnose pediatric obstructive sleep apnea: Systematic review and meta-analysis;gutiérrez-tobal;Pediatr Pulmonol,2021

3. Comparison of detrended fluctuation analysis and spectral analysis for heart rate variability in sleep and sleep apnea

4. REM and NREM sleep-state distribution of respiratory events in habitually snoring school-aged community children

5. Sleep stage classification in children using photo plethysmogram pulse rate variability;dehkordi;Comput Cardiol (2010),2014

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