Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost

Producción Científica

Detalles Bibliográficos
Autores: Jimenez García, Jorge, Gutierrez Tobal, Gonzalo César, García Gadañón, María, Kheirandish Gozal, Leila, Martín Montero, Adrián, Álvarez González, Daniel, Campo Matias, Félix del, Gozal, David, Hornero Sánchez, Roberto
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:España
Institución:Universidad de Valladolid
Repositorio:UVaDOC. Repositorio Documental de la Universidad de Valladolid
OAI Identifier:oai:uvadoc.uva.es:10324/58999
Acceso en línea:https://doi.org/10.3390/e22060670
https://uvadoc.uva.es/handle/10324/58999
Access Level:acceso abierto
Palabra clave:Pediatría
Pneumology/Respiratory System
Sleep apnea–hypopnea syndrome
Oximetry
AdaBoost
Airflow
Síndrome de apnea-hipopnea del sueño
Oximetría
Flujo de aire
32 Ciencias Médicas
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spelling Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoostJimenez García, JorgeGutierrez Tobal, Gonzalo CésarGarcía Gadañón, MaríaKheirandish Gozal, LeilaMartín Montero, AdriánÁlvarez González, DanielCampo Matias, Félix delGozal, DavidHornero Sánchez, RobertoPediatríaPneumology/Respiratory SystemSleep apnea–hypopnea syndromeOximetryAdaBoostAirflowSíndrome de apnea-hipopnea del sueñoOximetríaFlujo de aire32 Ciencias MédicasProducción CientíficaThe reference standard to diagnose pediatric Obstructive Sleep Apnea (OSA) syndrome is an overnight polysomnographic evaluation. When polysomnography is either unavailable or has limited availability, OSA screening may comprise the automatic analysis of a minimum number of signals. The primary objective of this study was to evaluate the complementarity of airflow (AF) and oximetry (SpO2) signals to automatically detect pediatric OSA. Additionally, a secondary goal was to assess the utility of a multiclass AdaBoost classifier to predict OSA severity in children. We extracted the same features from AF and SpO2 signals from 974 pediatric subjects. We also obtained the 3% Oxygen Desaturation Index (ODI) as a common clinically used variable. Then, feature selection was conducted using the Fast Correlation-Based Filter method and AdaBoost classifiers were evaluated. Models combining ODI 3% and AF features outperformed the diagnostic performance of each signal alone, reaching 0.39 Cohens’s kappa in the four-class classification task. OSA vs. No OSA accuracies reached 81.28%, 82.05% and 90.26% in the apnea–hypopnea index cutoffs 1, 5 and 10 events/h, respectively. The most relevant information from SpO2 was redundant with ODI 3%, and AF was complementary to them. Thus, the joint analysis of AF and SpO2 enhanced the diagnostic performance of each signal alone using AdaBoost, thereby enabling a potential screening alternative for OSA in children.Ministerio de Ciencia e Innovación - FEDER (DPI2017-84280-R y RTC-2017-6516-1)Comisión Europea - FEDER (Programa de Cooperación Interreg V-A España-Portugal POCTEP 2014–2020)Ministerio de Ciencia e Innovación - Ministerio de Universidades (PRE2018-085219)US National Institutes of Health (grants HL130984 and HL140548)MDPI2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://doi.org/10.3390/e22060670https://uvadoc.uva.es/handle/10324/58999reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolidinstname:Universidad de ValladolidIngléshttps://www.mdpi.com/1099-4300/22/6/670info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:uvadoc.uva.es:10324/589992026-06-13T12:44:47Z
dc.title.none.fl_str_mv Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
title Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
spellingShingle Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
Jimenez García, Jorge
Pediatría
Pneumology/Respiratory System
Sleep apnea–hypopnea syndrome
Oximetry
AdaBoost
Airflow
Síndrome de apnea-hipopnea del sueño
Oximetría
Flujo de aire
32 Ciencias Médicas
title_short Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
title_full Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
title_fullStr Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
title_full_unstemmed Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
title_sort Assessment of airflow and oximetry signals to detect pediatric sleep apnea-hypopnea syndrome using AdaBoost
dc.creator.none.fl_str_mv Jimenez García, Jorge
Gutierrez Tobal, Gonzalo César
García Gadañón, María
Kheirandish Gozal, Leila
Martín Montero, Adrián
Álvarez González, Daniel
Campo Matias, Félix del
Gozal, David
Hornero Sánchez, Roberto
author Jimenez García, Jorge
author_facet Jimenez García, Jorge
Gutierrez Tobal, Gonzalo César
García Gadañón, María
Kheirandish Gozal, Leila
Martín Montero, Adrián
Álvarez González, Daniel
Campo Matias, Félix del
Gozal, David
Hornero Sánchez, Roberto
author_role author
author2 Gutierrez Tobal, Gonzalo César
García Gadañón, María
Kheirandish Gozal, Leila
Martín Montero, Adrián
Álvarez González, Daniel
Campo Matias, Félix del
Gozal, David
Hornero Sánchez, Roberto
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Pediatría
Pneumology/Respiratory System
Sleep apnea–hypopnea syndrome
Oximetry
AdaBoost
Airflow
Síndrome de apnea-hipopnea del sueño
Oximetría
Flujo de aire
32 Ciencias Médicas
topic Pediatría
Pneumology/Respiratory System
Sleep apnea–hypopnea syndrome
Oximetry
AdaBoost
Airflow
Síndrome de apnea-hipopnea del sueño
Oximetría
Flujo de aire
32 Ciencias Médicas
description Producción Científica
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.3390/e22060670
https://uvadoc.uva.es/handle/10324/58999
url https://doi.org/10.3390/e22060670
https://uvadoc.uva.es/handle/10324/58999
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv https://www.mdpi.com/1099-4300/22/6/670
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:UVaDOC. Repositorio Documental de la Universidad de Valladolid
instname:Universidad de Valladolid
instname_str Universidad de Valladolid
reponame_str UVaDOC. Repositorio Documental de la Universidad de Valladolid
collection UVaDOC. Repositorio Documental de la Universidad de Valladolid
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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