Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation

Background and Objectives: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a growing healthcare burden worldwide. It is often asymptomatic and may appear as episodes of very short duration; hence, the development of methods for its automatic detection is a challenging re...

Descripción completa

Detalles Bibliográficos
Autores: García Teruel, Manuel, Ródenas García, Juan, Alcaraz Martínez, Raúl, Rieta Ibáñez, José Joaquín
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/12871
Acceso en línea:http://hdl.handle.net/10578/12871
Access Level:acceso embargado
Palabra clave:Atrial fibrillation
Automatic detection
Electrocardiogram
Relative wavelet energy
Stationary wavelet transform
id ES_a24d2d2859e8ca9ff316d5c8f8e39b61
oai_identifier_str oai:ruidera.uclm.es:10578/12871
network_acronym_str ES
network_name_str España
repository_id_str
spelling Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial FibrillationGarcía Teruel, ManuelRódenas García, JuanAlcaraz Martínez, RaúlRieta Ibáñez, José JoaquínAtrial fibrillationAutomatic detectionElectrocardiogramRelative wavelet energyStationary wavelet transformBackground and Objectives: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a growing healthcare burden worldwide. It is often asymptomatic and may appear as episodes of very short duration; hence, the development of methods for its automatic detection is a challenging requirement to achieve early diagnosis and treatment strategies.The present work introduces a novel method exploiting the relative wavelet energy (RWE) to automatically detect AF episodes of a wide variety in length. Methods: The proposed method analyzes the atrial activity of the surface electrocardiogram (ECG), i.e., theTQ interval, thus being independent on the ventricular activity.To improve its performance under noisy recordings, signal averaging techniques were applied.The method?s performance has been tested with synthesized recordings under different AF variable conditions, such as the heart rate, its variability, the atrial activity amplitude or the presence of noise. Next, the method was tested with real ECG recordings. Results: Results proved that the RWE provided a robust automatic detection of AF under wide ranges of heart rates, atrial activity amplitudes as well as noisy recordings. Moreover, the method?s detection delay proved to be shorter than most of previous works. A trade-off between detection delay and noise robustness was reached by averaging 15 TQ intervals. Under these conditions, AF was detected in less than 7 beats, with an accuracy higher than 90%, which is comparable to previous works. Conclusions: Unlike most of previous works, which were mainly based on quantifying the irregular ventricular response during AF, the proposed metric presents two major advantages.First, it can perform successfully even under heart rates with no variability. Second,it consists of a single metric, thus turning its clinical interpretation and real-time implementation easier than previous methods requiring combined indices under complex classifiers.Elsevier201720172016info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttp://hdl.handle.net/10578/12871reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglésinfo:eu-repo/semantics/embargoedAccessoai:ruidera.uclm.es:10578/128712026-05-27T07:36:41Z
dc.title.none.fl_str_mv Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
title Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
spellingShingle Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
García Teruel, Manuel
Atrial fibrillation
Automatic detection
Electrocardiogram
Relative wavelet energy
Stationary wavelet transform
title_short Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
title_full Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
title_fullStr Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
title_full_unstemmed Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
title_sort Application of the Relative Wavelet Energy to 1 Heart Rate Independent Detection of Atrial Fibrillation
dc.creator.none.fl_str_mv García Teruel, Manuel
Ródenas García, Juan
Alcaraz Martínez, Raúl
Rieta Ibáñez, José Joaquín
author García Teruel, Manuel
author_facet García Teruel, Manuel
Ródenas García, Juan
Alcaraz Martínez, Raúl
Rieta Ibáñez, José Joaquín
author_role author
author2 Ródenas García, Juan
Alcaraz Martínez, Raúl
Rieta Ibáñez, José Joaquín
author2_role author
author
author
dc.subject.none.fl_str_mv Atrial fibrillation
Automatic detection
Electrocardiogram
Relative wavelet energy
Stationary wavelet transform
topic Atrial fibrillation
Automatic detection
Electrocardiogram
Relative wavelet energy
Stationary wavelet transform
description Background and Objectives: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a growing healthcare burden worldwide. It is often asymptomatic and may appear as episodes of very short duration; hence, the development of methods for its automatic detection is a challenging requirement to achieve early diagnosis and treatment strategies.The present work introduces a novel method exploiting the relative wavelet energy (RWE) to automatically detect AF episodes of a wide variety in length. Methods: The proposed method analyzes the atrial activity of the surface electrocardiogram (ECG), i.e., theTQ interval, thus being independent on the ventricular activity.To improve its performance under noisy recordings, signal averaging techniques were applied.The method?s performance has been tested with synthesized recordings under different AF variable conditions, such as the heart rate, its variability, the atrial activity amplitude or the presence of noise. Next, the method was tested with real ECG recordings. Results: Results proved that the RWE provided a robust automatic detection of AF under wide ranges of heart rates, atrial activity amplitudes as well as noisy recordings. Moreover, the method?s detection delay proved to be shorter than most of previous works. A trade-off between detection delay and noise robustness was reached by averaging 15 TQ intervals. Under these conditions, AF was detected in less than 7 beats, with an accuracy higher than 90%, which is comparable to previous works. Conclusions: Unlike most of previous works, which were mainly based on quantifying the irregular ventricular response during AF, the proposed metric presents two major advantages.First, it can perform successfully even under heart rates with no variability. Second,it consists of a single metric, thus turning its clinical interpretation and real-time implementation easier than previous methods requiring combined indices under complex classifiers.
publishDate 2016
dc.date.none.fl_str_mv 2016
2017
2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10578/12871
url http://hdl.handle.net/10578/12871
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv info:eu-repo/semantics/embargoedAccess
eu_rights_str_mv embargoedAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
collection RUIdeRA. Repositorio Institucional de la UCLM
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869415251762479104
score 15,300719

Similares en LA Referencia