dc.contributor.author
Ravelo-García, Antonio G.
dc.contributor.author
Kraemer, Jan F.
dc.contributor.author
Navarro-Mesa, Juan L.
dc.contributor.author
Hernández-Pérez, Eduardo
dc.contributor.author
Navarro-Esteva, Javier
dc.contributor.author
Juliá-Serdá, Gabriel
dc.contributor.author
Penzel, Thomas
dc.contributor.author
Wessel, Niels
dc.date.accessioned
2018-06-08T04:04:30Z
dc.date.available
2015-07-28T11:41:19.559Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/16529
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-20710
dc.description.abstract
A diagnostic system for sleep apnea based on oxygen saturation and RR
intervals obtained from the EKG (electrocardiogram) is proposed with the goal
to detect and quantify minute long segments of sleep with breathing pauses. We
measured the discriminative capacity of combinations of features obtained from
RR series and oximetry to evaluate improvements of the performance compared to
oximetry-based features alone. Time and frequency domain variables derived
from oxygen saturation (SpO2) as well as linear and non-linear variables
describing the RR series have been explored in recordings from 70 patients
with suspected sleep apnea. We applied forward feature selection in order to
select a minimal set of variables that are able to locate patterns indicating
respiratory pauses. Linear discriminant analysis (LDA) was used to classify
the presence of apnea during specific segments. The system will finally
provide a global score indicating the presence of clinically significant apnea
integrating the segment based apnea detection. LDA results in an accuracy of
87%; sensitivity of 76% and specificity of 91% (AUC = 0.90) with a global
classification of 97% when only oxygen saturation is used. In case of
additionally including features from the RR series; the system performance
improves to an accuracy of 87%; sensitivity of 73% and specificity of 92% (AUC
= 0.92), with a global classification rate of 100%.
en
dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
dc.subject
oxygen saturation
dc.subject
feature selection
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit
dc.title
Oxygen Saturation and RR Intervals Feature Selection for Sleep Apnea Detection
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation
Entropy. - 17 (2015), 5, S. 2932-2957
dcterms.bibliographicCitation.doi
10.3390/e17052932
dcterms.bibliographicCitation.url
http://www.mdpi.com/1099-4300/17/5/2932
refubium.affiliation
Charité - Universitätsmedizin Berlin
de
refubium.mycore.fudocsId
FUDOCS_document_000000022893
refubium.note.author
Der Artikel wurde in einer Open-Access-Zeitschrift publiziert
refubium.resourceType.isindependentpub
no
refubium.mycore.derivateId
FUDOCS_derivate_000000005255
dcterms.accessRights.openaire
open access