ECGMiner: A flexible software for accurately digitizing ECG

The electrocardiogram (ECG) is the most important non-invasive method for elucidating information about heart and cardiovascular disease diagnosis. Typically, the ECG system manufacturing companies provide ECG images, but store the numerical data in a proprietary format that is not interpretable and...

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Detalles Bibliográficos
Autores: Santamónica, Adolfo F, Carratalá-Sáez, Rocío, Larriba, Yolanda, Pérez-Castellanos, Alberto, Rueda, Cristina
Tipo de recurso: artículo
Fecha de publicación:2024
País:España
Institución:Conselleria de Salut i Consum del Govern de les Illes Balears
Repositorio:Docusalut
Idioma:inglés
OAI Identifier:oai:docusalut.com:20.500.13003/20268
Acceso en línea:https://hdl.handle.net/20.500.13003/20268
Access Level:acceso abierto
Palabra clave:Software
Signal Processing, Computer-Assisted
Databases, Factual
Algorithms
Electrocardiography
Procesamiento de Señales Asistido por Computador
Electrocardiografía
Algoritmos
Programas Informáticos
Bases de Datos Factuales
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spelling ECGMiner: A flexible software for accurately digitizing ECGSantamónica, Adolfo FCarratalá-Sáez, RocíoLarriba, YolandaPérez-Castellanos, AlbertoRueda, CristinaSoftwareSignal Processing, Computer-AssistedDatabases, FactualAlgorithmsElectrocardiographyProcesamiento de Señales Asistido por ComputadorElectrocardiografíaAlgoritmosProgramas InformáticosBases de Datos FactualesThe electrocardiogram (ECG) is the most important non-invasive method for elucidating information about heart and cardiovascular disease diagnosis. Typically, the ECG system manufacturing companies provide ECG images, but store the numerical data in a proprietary format that is not interpretable and is not therefore useful for automatic diagnosis. There have been many efforts to digitize paper-based ECGs. The main limitations of previous works in ECG digitization are that they require manual selection of the regions of interest, only partly provide signal digitization, and offer limited accuracy. We have developed the ECGMiner, an open-source software to digitize ECG images. It is precise, fast, and simple to use. This software digitizes ECGs in four steps: 1) recognizing the image composition; 2) removing the gridline; 3) extracting the signals; 4) post-processing and storing the data. We have evaluated the ECGMiner digitization capabilities using the Pearson Correlation Coefficient (PCC) and the Root Mean Square Error (RMSE) measures, and we consider ECG from two large, public, and widely used databases, LUDB and PTB-XL. The actual and digitized values of signals in both databases have been compared. The software's ability to correctly identify the location of characteristic waves has also been validated. Specifically, the PCC values are between 0.971 and 0.995, and the RMSE values are between 0.011 and 0.031 mV. The ECGMiner software presented in this paper is open access, easy to install, easy to use, and capable of precisely recovering the paper-based/digital ECG signal data, regardless of the input format and signal complexity. ECGMiner outperforms existing digitization algorithms in terms of PCC and RMSE values.Elsevier20242024-04-0120242024-04-01research articlehttp://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.13003/20268reponame:Docusalutinstname:Conselleria de Salut i Consum del Govern de les Illes BalearsInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:docusalut.com:20.500.13003/202682026-06-22T12:44:07Z
dc.title.none.fl_str_mv ECGMiner: A flexible software for accurately digitizing ECG
title ECGMiner: A flexible software for accurately digitizing ECG
spellingShingle ECGMiner: A flexible software for accurately digitizing ECG
Santamónica, Adolfo F
Software
Signal Processing, Computer-Assisted
Databases, Factual
Algorithms
Electrocardiography
Procesamiento de Señales Asistido por Computador
Electrocardiografía
Algoritmos
Programas Informáticos
Bases de Datos Factuales
title_short ECGMiner: A flexible software for accurately digitizing ECG
title_full ECGMiner: A flexible software for accurately digitizing ECG
title_fullStr ECGMiner: A flexible software for accurately digitizing ECG
title_full_unstemmed ECGMiner: A flexible software for accurately digitizing ECG
title_sort ECGMiner: A flexible software for accurately digitizing ECG
dc.creator.none.fl_str_mv Santamónica, Adolfo F
Carratalá-Sáez, Rocío
Larriba, Yolanda
Pérez-Castellanos, Alberto
Rueda, Cristina
author Santamónica, Adolfo F
author_facet Santamónica, Adolfo F
Carratalá-Sáez, Rocío
Larriba, Yolanda
Pérez-Castellanos, Alberto
Rueda, Cristina
author_role author
author2 Carratalá-Sáez, Rocío
Larriba, Yolanda
Pérez-Castellanos, Alberto
Rueda, Cristina
author2_role author
author
author
author
dc.contributor.none.fl_str_mv
dc.subject.none.fl_str_mv Software
Signal Processing, Computer-Assisted
Databases, Factual
Algorithms
Electrocardiography
Procesamiento de Señales Asistido por Computador
Electrocardiografía
Algoritmos
Programas Informáticos
Bases de Datos Factuales
topic Software
Signal Processing, Computer-Assisted
Databases, Factual
Algorithms
Electrocardiography
Procesamiento de Señales Asistido por Computador
Electrocardiografía
Algoritmos
Programas Informáticos
Bases de Datos Factuales
description The electrocardiogram (ECG) is the most important non-invasive method for elucidating information about heart and cardiovascular disease diagnosis. Typically, the ECG system manufacturing companies provide ECG images, but store the numerical data in a proprietary format that is not interpretable and is not therefore useful for automatic diagnosis. There have been many efforts to digitize paper-based ECGs. The main limitations of previous works in ECG digitization are that they require manual selection of the regions of interest, only partly provide signal digitization, and offer limited accuracy. We have developed the ECGMiner, an open-source software to digitize ECG images. It is precise, fast, and simple to use. This software digitizes ECGs in four steps: 1) recognizing the image composition; 2) removing the gridline; 3) extracting the signals; 4) post-processing and storing the data. We have evaluated the ECGMiner digitization capabilities using the Pearson Correlation Coefficient (PCC) and the Root Mean Square Error (RMSE) measures, and we consider ECG from two large, public, and widely used databases, LUDB and PTB-XL. The actual and digitized values of signals in both databases have been compared. The software's ability to correctly identify the location of characteristic waves has also been validated. Specifically, the PCC values are between 0.971 and 0.995, and the RMSE values are between 0.011 and 0.031 mV. The ECGMiner software presented in this paper is open access, easy to install, easy to use, and capable of precisely recovering the paper-based/digital ECG signal data, regardless of the input format and signal complexity. ECGMiner outperforms existing digitization algorithms in terms of PCC and RMSE values.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-04-01
2024
2024-04-01
dc.type.none.fl_str_mv research article
http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.13003/20268
url https://hdl.handle.net/20.500.13003/20268
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Docusalut
instname:Conselleria de Salut i Consum del Govern de les Illes Balears
instname_str Conselleria de Salut i Consum del Govern de les Illes Balears
reponame_str Docusalut
collection Docusalut
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,228081

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