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Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients
In this paper, we thoroughly analyze the detection of sleep apnea events in the context of Obstructive Sleep Apnea (OSA), which is considered a public health problem because of its high prevalence and serious health implications. We especially evaluate patients who do not always show desaturations d...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181515/ https://www.ncbi.nlm.nih.gov/pubmed/37177472 http://dx.doi.org/10.3390/s23094267 |
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author | Martín-González, Sofía Ravelo-García, Antonio G. Navarro-Mesa, Juan L. Hernández-Pérez, Eduardo |
author_facet | Martín-González, Sofía Ravelo-García, Antonio G. Navarro-Mesa, Juan L. Hernández-Pérez, Eduardo |
author_sort | Martín-González, Sofía |
collection | PubMed |
description | In this paper, we thoroughly analyze the detection of sleep apnea events in the context of Obstructive Sleep Apnea (OSA), which is considered a public health problem because of its high prevalence and serious health implications. We especially evaluate patients who do not always show desaturations during apneic episodes (non-desaturating patients). For this purpose, we use a database (HuGCDN2014-OXI) that includes desaturating and non-desaturating patients, and we use the widely used Physionet Apnea Dataset for a meaningful comparison with prior work. Our system combines features extracted from the Heart-Rate Variability (HRV) and SpO(2), and it explores their potential to characterize desaturating and non-desaturating events. The HRV-based features include spectral, cepstral, and nonlinear information (Detrended Fluctuation Analysis (DFA) and Recurrence Quantification Analysis (RQA)). SpO(2)-based features include temporal (variance) and spectral information. The features feed a Linear Discriminant Analysis (LDA) classifier. The goal is to evaluate the effect of using these features either individually or in combination, especially in non-desaturating patients. The main results for the detection of apneic events are: (a) Physionet success rate of 96.19%, sensitivity of 95.74% and specificity of 95.25% (Area Under Curve (AUC): 0.99); (b) HuGCDN2014-OXI of 87.32%, 83.81% and 88.55% (AUC: 0.934), respectively. The best results for the global diagnosis of OSA patients (HuGCDN2014-OXI) are: success rate of 95.74%, sensitivity of 100%, and specificity of 89.47%. We conclude that combining both features is the most accurate option, especially when there are non-desaturating patterns among the recordings under study. |
format | Online Article Text |
id | pubmed-10181515 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-101815152023-05-13 Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients Martín-González, Sofía Ravelo-García, Antonio G. Navarro-Mesa, Juan L. Hernández-Pérez, Eduardo Sensors (Basel) Article In this paper, we thoroughly analyze the detection of sleep apnea events in the context of Obstructive Sleep Apnea (OSA), which is considered a public health problem because of its high prevalence and serious health implications. We especially evaluate patients who do not always show desaturations during apneic episodes (non-desaturating patients). For this purpose, we use a database (HuGCDN2014-OXI) that includes desaturating and non-desaturating patients, and we use the widely used Physionet Apnea Dataset for a meaningful comparison with prior work. Our system combines features extracted from the Heart-Rate Variability (HRV) and SpO(2), and it explores their potential to characterize desaturating and non-desaturating events. The HRV-based features include spectral, cepstral, and nonlinear information (Detrended Fluctuation Analysis (DFA) and Recurrence Quantification Analysis (RQA)). SpO(2)-based features include temporal (variance) and spectral information. The features feed a Linear Discriminant Analysis (LDA) classifier. The goal is to evaluate the effect of using these features either individually or in combination, especially in non-desaturating patients. The main results for the detection of apneic events are: (a) Physionet success rate of 96.19%, sensitivity of 95.74% and specificity of 95.25% (Area Under Curve (AUC): 0.99); (b) HuGCDN2014-OXI of 87.32%, 83.81% and 88.55% (AUC: 0.934), respectively. The best results for the global diagnosis of OSA patients (HuGCDN2014-OXI) are: success rate of 95.74%, sensitivity of 100%, and specificity of 89.47%. We conclude that combining both features is the most accurate option, especially when there are non-desaturating patterns among the recordings under study. MDPI 2023-04-25 /pmc/articles/PMC10181515/ /pubmed/37177472 http://dx.doi.org/10.3390/s23094267 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Martín-González, Sofía Ravelo-García, Antonio G. Navarro-Mesa, Juan L. Hernández-Pérez, Eduardo Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients |
title | Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients |
title_full | Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients |
title_fullStr | Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients |
title_full_unstemmed | Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients |
title_short | Combining Heart Rate Variability and Oximetry to Improve Apneic Event Screening in Non-Desaturating Patients |
title_sort | combining heart rate variability and oximetry to improve apneic event screening in non-desaturating patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10181515/ https://www.ncbi.nlm.nih.gov/pubmed/37177472 http://dx.doi.org/10.3390/s23094267 |
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