Cargando…
A Detector for Premature Atrial and Ventricular Complexes
The relationship between premature atrial complexes (PACs) and atrial fibrillation (AF), stroke and myocardium degradation is unclear. Current PAC detectors are beat classifiers that attain low sensitivity on PAC detection. The lack of a proper PAC detector hinders the study of the implications of t...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243653/ https://www.ncbi.nlm.nih.gov/pubmed/34220543 http://dx.doi.org/10.3389/fphys.2021.678558 |
_version_ | 1783715788904988672 |
---|---|
author | García-Isla, Guadalupe Mainardi, Luca Corino, Valentina D. A. |
author_facet | García-Isla, Guadalupe Mainardi, Luca Corino, Valentina D. A. |
author_sort | García-Isla, Guadalupe |
collection | PubMed |
description | The relationship between premature atrial complexes (PACs) and atrial fibrillation (AF), stroke and myocardium degradation is unclear. Current PAC detectors are beat classifiers that attain low sensitivity on PAC detection. The lack of a proper PAC detector hinders the study of the implications of this event and its monitoring. In this work a PAC and ventricular detector is presented. Two PhysioNet open-source databases were used: the long-term ST database (LTSTDB) and the supraventricular arrhythmia database (SVDB). A combination of heart rate variability (HRV) and morphological features were used to classify beats. Morphological features were extracted from the ECG as well as on the 4th scale of the discrete wavelet transform (DWT). After feature selection, a random forest algorithm was trained for a binary classification of PAC (S) vs. others and for a multi-labels classification to discriminate between normal (N), S and ventricular (V) beats. The algorithm was tested in a 10-fold cross-validation following a patient-wise train-test division (i.e., no beats belonging to the same patient were included both in the test and train set). The resultant median sensitivity, specificity and positive predictive value (PPV) were 99.29, 99.54, and 100% for (N), 95.83, 99.39, and 35.68% for (S), 100, 99.90, and 79.63% for (V). The proposed method attains a greater PAC and ventricular beat sensitivity and PPV than the state-of-the-art classifiers. |
format | Online Article Text |
id | pubmed-8243653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82436532021-07-01 A Detector for Premature Atrial and Ventricular Complexes García-Isla, Guadalupe Mainardi, Luca Corino, Valentina D. A. Front Physiol Physiology The relationship between premature atrial complexes (PACs) and atrial fibrillation (AF), stroke and myocardium degradation is unclear. Current PAC detectors are beat classifiers that attain low sensitivity on PAC detection. The lack of a proper PAC detector hinders the study of the implications of this event and its monitoring. In this work a PAC and ventricular detector is presented. Two PhysioNet open-source databases were used: the long-term ST database (LTSTDB) and the supraventricular arrhythmia database (SVDB). A combination of heart rate variability (HRV) and morphological features were used to classify beats. Morphological features were extracted from the ECG as well as on the 4th scale of the discrete wavelet transform (DWT). After feature selection, a random forest algorithm was trained for a binary classification of PAC (S) vs. others and for a multi-labels classification to discriminate between normal (N), S and ventricular (V) beats. The algorithm was tested in a 10-fold cross-validation following a patient-wise train-test division (i.e., no beats belonging to the same patient were included both in the test and train set). The resultant median sensitivity, specificity and positive predictive value (PPV) were 99.29, 99.54, and 100% for (N), 95.83, 99.39, and 35.68% for (S), 100, 99.90, and 79.63% for (V). The proposed method attains a greater PAC and ventricular beat sensitivity and PPV than the state-of-the-art classifiers. Frontiers Media S.A. 2021-06-16 /pmc/articles/PMC8243653/ /pubmed/34220543 http://dx.doi.org/10.3389/fphys.2021.678558 Text en Copyright © 2021 García-Isla, Mainardi and Corino. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology García-Isla, Guadalupe Mainardi, Luca Corino, Valentina D. A. A Detector for Premature Atrial and Ventricular Complexes |
title | A Detector for Premature Atrial and Ventricular Complexes |
title_full | A Detector for Premature Atrial and Ventricular Complexes |
title_fullStr | A Detector for Premature Atrial and Ventricular Complexes |
title_full_unstemmed | A Detector for Premature Atrial and Ventricular Complexes |
title_short | A Detector for Premature Atrial and Ventricular Complexes |
title_sort | detector for premature atrial and ventricular complexes |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243653/ https://www.ncbi.nlm.nih.gov/pubmed/34220543 http://dx.doi.org/10.3389/fphys.2021.678558 |
work_keys_str_mv | AT garciaislaguadalupe adetectorforprematureatrialandventricularcomplexes AT mainardiluca adetectorforprematureatrialandventricularcomplexes AT corinovalentinada adetectorforprematureatrialandventricularcomplexes AT garciaislaguadalupe detectorforprematureatrialandventricularcomplexes AT mainardiluca detectorforprematureatrialandventricularcomplexes AT corinovalentinada detectorforprematureatrialandventricularcomplexes |