ECG-Based Identification of Sudden Cardiac Death through Sparse Representations

Sudden Cardiac Death (SCD) is an unexpected sudden death due to a loss of heart function and represents more than 50% of the deaths from cardiovascular diseases. Since cardiovascular problems change the features in the electrical signal of the heart, if significant changes are found with respect to...

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Autores principales:	Josue R. Velázquez-González, Hayde Peregrina-Barreto, Jose J. Rangel-Magdaleno, Juan M. Ramirez-Cortes, Juan P. Amezquita-Sanchez
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	ECG signals sparse representations sudden cardiac death Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/3a1812e0fa20449bb13aef89e67ddd31
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spelling	oai:doaj.org-article:3a1812e0fa20449bb13aef89e67ddd312021-11-25T18:58:19ZECG-Based Identification of Sudden Cardiac Death through Sparse Representations10.3390/s212276661424-8220https://doaj.org/article/3a1812e0fa20449bb13aef89e67ddd312021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7666https://doaj.org/toc/1424-8220Sudden Cardiac Death (SCD) is an unexpected sudden death due to a loss of heart function and represents more than 50% of the deaths from cardiovascular diseases. Since cardiovascular problems change the features in the electrical signal of the heart, if significant changes are found with respect to a reference signal (healthy), then it is possible to indicate in advance a possible SCD occurrence. This work proposes SCD identification using Electrocardiogram (ECG) signals and a sparse representation technique. Moreover, the use of fixed feature ranking is avoided by considering a dictionary as a flexible set of features where each sparse representation could be seen as a dynamic feature extraction process. In this way, the involved features may differ within the dictionary’s margin of similarity, which is better-suited to the large number of variations that an ECG signal contains. The experiments were carried out using the ECG signals from the MIT/BIH-SCDH and the MIT/BIH-NSR databases. The results show that it is possible to achieve a detection 30 min before the SCD event occurs, reaching an an accuracy of 95.3% under the common scheme, and 80.5% under the proposed multi-class scheme, thus being suitable for detecting a SCD episode in advance.Josue R. Velázquez-GonzálezHayde Peregrina-BarretoJose J. Rangel-MagdalenoJuan M. Ramirez-CortesJuan P. Amezquita-SanchezMDPI AGarticleECG signalssparse representationssudden cardiac deathChemical technologyTP1-1185ENSensors, Vol 21, Iss 7666, p 7666 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ECG signals sparse representations sudden cardiac death Chemical technology TP1-1185
spellingShingle	ECG signals sparse representations sudden cardiac death Chemical technology TP1-1185 Josue R. Velázquez-González Hayde Peregrina-Barreto Jose J. Rangel-Magdaleno Juan M. Ramirez-Cortes Juan P. Amezquita-Sanchez ECG-Based Identification of Sudden Cardiac Death through Sparse Representations
description	Sudden Cardiac Death (SCD) is an unexpected sudden death due to a loss of heart function and represents more than 50% of the deaths from cardiovascular diseases. Since cardiovascular problems change the features in the electrical signal of the heart, if significant changes are found with respect to a reference signal (healthy), then it is possible to indicate in advance a possible SCD occurrence. This work proposes SCD identification using Electrocardiogram (ECG) signals and a sparse representation technique. Moreover, the use of fixed feature ranking is avoided by considering a dictionary as a flexible set of features where each sparse representation could be seen as a dynamic feature extraction process. In this way, the involved features may differ within the dictionary’s margin of similarity, which is better-suited to the large number of variations that an ECG signal contains. The experiments were carried out using the ECG signals from the MIT/BIH-SCDH and the MIT/BIH-NSR databases. The results show that it is possible to achieve a detection 30 min before the SCD event occurs, reaching an an accuracy of 95.3% under the common scheme, and 80.5% under the proposed multi-class scheme, thus being suitable for detecting a SCD episode in advance.
format	article
author	Josue R. Velázquez-González Hayde Peregrina-Barreto Jose J. Rangel-Magdaleno Juan M. Ramirez-Cortes Juan P. Amezquita-Sanchez
author_facet	Josue R. Velázquez-González Hayde Peregrina-Barreto Jose J. Rangel-Magdaleno Juan M. Ramirez-Cortes Juan P. Amezquita-Sanchez
author_sort	Josue R. Velázquez-González
title	ECG-Based Identification of Sudden Cardiac Death through Sparse Representations
title_short	ECG-Based Identification of Sudden Cardiac Death through Sparse Representations
title_full	ECG-Based Identification of Sudden Cardiac Death through Sparse Representations
title_fullStr	ECG-Based Identification of Sudden Cardiac Death through Sparse Representations
title_full_unstemmed	ECG-Based Identification of Sudden Cardiac Death through Sparse Representations
title_sort	ecg-based identification of sudden cardiac death through sparse representations
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3a1812e0fa20449bb13aef89e67ddd31
work_keys_str_mv	AT josuervelazquezgonzalez ecgbasedidentificationofsuddencardiacdeaththroughsparserepresentations AT haydeperegrinabarreto ecgbasedidentificationofsuddencardiacdeaththroughsparserepresentations AT josejrangelmagdaleno ecgbasedidentificationofsuddencardiacdeaththroughsparserepresentations AT juanmramirezcortes ecgbasedidentificationofsuddencardiacdeaththroughsparserepresentations AT juanpamezquitasanchez ecgbasedidentificationofsuddencardiacdeaththroughsparserepresentations
_version_	1718410456751669248

ECG-Based Identification of Sudden Cardiac Death through Sparse Representations

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