Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry

Autores
Schlotthauer, Gaston; Di Persia, Leandro Ezequiel; Larrateguy, Luis Darío; Milone, Diego Humberto
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea–hypopnea syndrome. It is important to have automatic detection methods that allows the screening for this syndrome, reducing the need of the expensive polysomnography based studies. In this paper a novel recognition method based on the empirical mode decomposition of the pulse oximetry signal is proposed. The desaturations produce a very specific wave pattern that is extracted in the modes of the decomposition. Using this information, a detector based on properly selected thresholds and a set of simple rules is built. The oxygen desaturation index constructed from these detections produces a detector for obstructive sleep apnea–hypopnea syndrome with high sensitivity (0.838) and specificity (0.855) and yields better results than standard desaturation detection approaches.
Fil: Schlotthauer, Gaston. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina
Fil: Di Persia, Leandro Ezequiel. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Larrateguy, Luis Darío. Centro de Medicina Respiratoria; Argentina
Fil: Milone, Diego Humberto. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Materia
Sleep Apnea
Empirical Mode Decomposition
Pulse Oximetry
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/31749
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/31749
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetrySchlotthauer, GastonDi Persia, Leandro EzequielLarrateguy, Luis DaríoMilone, Diego HumbertoSleep ApneaEmpirical Mode DecompositionPulse Oximetryhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea–hypopnea syndrome. It is important to have automatic detection methods that allows the screening for this syndrome, reducing the need of the expensive polysomnography based studies. In this paper a novel recognition method based on the empirical mode decomposition of the pulse oximetry signal is proposed. The desaturations produce a very specific wave pattern that is extracted in the modes of the decomposition. Using this information, a detector based on properly selected thresholds and a set of simple rules is built. The oxygen desaturation index constructed from these detections produces a detector for obstructive sleep apnea–hypopnea syndrome with high sensitivity (0.838) and specificity (0.855) and yields better results than standard desaturation detection approaches.Fil: Schlotthauer, Gaston. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; ArgentinaFil: Di Persia, Leandro Ezequiel. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Larrateguy, Luis Darío. Centro de Medicina Respiratoria; ArgentinaFil: Milone, Diego Humberto. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaElsevier2014-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/31749Larrateguy, Luis Darío; Di Persia, Leandro Ezequiel; Schlotthauer, Gaston; Milone, Diego Humberto; Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry; Elsevier; Medical Engineering & Physics; 36; 8; 6-2014; 1074-10801350-4533CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1350453314001234info:eu-repo/semantics/altIdentifier/doi/10.1016/j.medengphy.2014.05.008info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:33:28Zoai:ri.conicet.gov.ar:11336/31749instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:33:28.689CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
title Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
spellingShingle Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
Schlotthauer, Gaston
Sleep Apnea
Empirical Mode Decomposition
Pulse Oximetry
title_short Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
title_full Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
title_fullStr Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
title_full_unstemmed Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
title_sort Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry
dc.creator.none.fl_str_mv Schlotthauer, Gaston
Di Persia, Leandro Ezequiel
Larrateguy, Luis Darío
Milone, Diego Humberto
author Schlotthauer, Gaston
author_facet Schlotthauer, Gaston
Di Persia, Leandro Ezequiel
Larrateguy, Luis Darío
Milone, Diego Humberto
author_role author
author2 Di Persia, Leandro Ezequiel
Larrateguy, Luis Darío
Milone, Diego Humberto
author2_role author
author
author
dc.subject.none.fl_str_mv Sleep Apnea
Empirical Mode Decomposition
Pulse Oximetry
topic Sleep Apnea
Empirical Mode Decomposition
Pulse Oximetry
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea–hypopnea syndrome. It is important to have automatic detection methods that allows the screening for this syndrome, reducing the need of the expensive polysomnography based studies. In this paper a novel recognition method based on the empirical mode decomposition of the pulse oximetry signal is proposed. The desaturations produce a very specific wave pattern that is extracted in the modes of the decomposition. Using this information, a detector based on properly selected thresholds and a set of simple rules is built. The oxygen desaturation index constructed from these detections produces a detector for obstructive sleep apnea–hypopnea syndrome with high sensitivity (0.838) and specificity (0.855) and yields better results than standard desaturation detection approaches.
Fil: Schlotthauer, Gaston. Universidad Nacional de Entre Ríos. Facultad de Ingeniería. Departamento de Matemática e Informática. Laboratorio de Señales y Dinámicas no Lineales; Argentina
Fil: Di Persia, Leandro Ezequiel. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
Fil: Larrateguy, Luis Darío. Centro de Medicina Respiratoria; Argentina
Fil: Milone, Diego Humberto. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Departamento de Informática. Laboratorio de Investigaciones en Señales e Inteligencia Computacional; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina
description Detection of desaturations on the pulse oximetry signal is of great importance for the diagnosis of sleep apneas. Using the counting of desaturations, an index can be built to help in the diagnosis of severe cases of obstructive sleep apnea–hypopnea syndrome. It is important to have automatic detection methods that allows the screening for this syndrome, reducing the need of the expensive polysomnography based studies. In this paper a novel recognition method based on the empirical mode decomposition of the pulse oximetry signal is proposed. The desaturations produce a very specific wave pattern that is extracted in the modes of the decomposition. Using this information, a detector based on properly selected thresholds and a set of simple rules is built. The oxygen desaturation index constructed from these detections produces a detector for obstructive sleep apnea–hypopnea syndrome with high sensitivity (0.838) and specificity (0.855) and yields better results than standard desaturation detection approaches.
publishDate 2014
dc.date.none.fl_str_mv 2014-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/31749
Larrateguy, Luis Darío; Di Persia, Leandro Ezequiel; Schlotthauer, Gaston; Milone, Diego Humberto; Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry; Elsevier; Medical Engineering & Physics; 36; 8; 6-2014; 1074-1080
1350-4533
CONICET Digital
CONICET
url http://hdl.handle.net/11336/31749
identifier_str_mv Larrateguy, Luis Darío; Di Persia, Leandro Ezequiel; Schlotthauer, Gaston; Milone, Diego Humberto; Screening of obstructive sleep apnea with empirical mode decomposition of pulse oximetry; Elsevier; Medical Engineering & Physics; 36; 8; 6-2014; 1074-1080
1350-4533
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1350453314001234
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.medengphy.2014.05.008
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844614350210334720
score 13.070432

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