Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation

This work presents open-source software that incorporates detection and delineation algorithms of characteristic points of QRS complexes and P and T waves in ECG recordings. The tool facilitates the identification of significant points in the ECG waves, allowing manual correction of the results base...

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Autores: Martínez Suárez, Frank, Alvarado Serrano, Carlos, Casas Piedrafita, Óscar|||0000-0002-0077-0561
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/427242
Acceso en línea:https://hdl.handle.net/2117/427242
https://dx.doi.org/10.1088/2057-1976/adb589
Access Level:acceso abierto
Palabra clave:ECG waves
QRS detection
P wave
T wave
Continuous wavelet transform
Splines
Àrees temàtiques de la UPC::Enginyeria biomèdica::Aparells mèdics::Aparells cardiovasculars
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network_acronym_str ES
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repository_id_str
spelling Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementationMartínez Suárez, FrankAlvarado Serrano, CarlosCasas Piedrafita, Óscar|||0000-0002-0077-0561ECG wavesQRS detectionP waveT waveContinuous wavelet transformSplinesÀrees temàtiques de la UPC::Enginyeria biomèdica::Aparells mèdics::Aparells cardiovascularsThis work presents open-source software that incorporates detection and delineation algorithms of characteristic points of QRS complexes and P and T waves in ECG recordings. The tool facilitates the identification of significant points in the ECG waves, allowing manual correction of the results based on user criteria, exporting the detected points, and a simultaneous visualization of the recordings and the obtained points. The main objective is to improve the management of long- and short-term recordings by reducing detection errors caused by noise, interference, and artifacts, while also providing the capability for manual results correction. To achieve these objectives, the software uses an SQL Server database, which efficiently manages the data, and detection and delineation algorithms based on the continuous wavelet transform with splines, along with alternatives to optimize processing time. The QRS complex detection algorithm was validated in a previous work with the manually annotated ECG databases: MIT-BIH Arrhythmia, European ST-T, and QT. The QRS detector obtained a Se = 99.91% and a P+ = 99.62% on the first channel of the MIT-BIH, ST-T and QT databases over the 986,930 QRS complexes analyzed. To evaluate the delineation algorithms of the characteristic points of QRS, P and T waves, the QT and PTB databases were used. The mean and standard deviations of the differences between the automatic and manual annotations by CSE experts were calculated. The mean errors range obtained was smaller than one sample (4 ms) to around two samples (8 ms); and the mean standard deviations range was around of two samples (8 ms) to six samples (24 ms).Institute of Physics (IOP)20252025-03-3120252025-03-28journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/427242https://dx.doi.org/10.1088/2057-1976/adb589reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4272422026-05-27T15:37:01Z
dc.title.none.fl_str_mv Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
title Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
spellingShingle Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
Martínez Suárez, Frank
ECG waves
QRS detection
P wave
T wave
Continuous wavelet transform
Splines
Àrees temàtiques de la UPC::Enginyeria biomèdica::Aparells mèdics::Aparells cardiovasculars
title_short Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
title_full Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
title_fullStr Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
title_full_unstemmed Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
title_sort Platform for detecting, managing, and manipulating characteristic points of the ECG waves through continuous wavelet transform implementation
dc.creator.none.fl_str_mv Martínez Suárez, Frank
Alvarado Serrano, Carlos
Casas Piedrafita, Óscar|||0000-0002-0077-0561
author Martínez Suárez, Frank
author_facet Martínez Suárez, Frank
Alvarado Serrano, Carlos
Casas Piedrafita, Óscar|||0000-0002-0077-0561
author_role author
author2 Alvarado Serrano, Carlos
Casas Piedrafita, Óscar|||0000-0002-0077-0561
author2_role author
author
dc.subject.none.fl_str_mv ECG waves
QRS detection
P wave
T wave
Continuous wavelet transform
Splines
Àrees temàtiques de la UPC::Enginyeria biomèdica::Aparells mèdics::Aparells cardiovasculars
topic ECG waves
QRS detection
P wave
T wave
Continuous wavelet transform
Splines
Àrees temàtiques de la UPC::Enginyeria biomèdica::Aparells mèdics::Aparells cardiovasculars
description This work presents open-source software that incorporates detection and delineation algorithms of characteristic points of QRS complexes and P and T waves in ECG recordings. The tool facilitates the identification of significant points in the ECG waves, allowing manual correction of the results based on user criteria, exporting the detected points, and a simultaneous visualization of the recordings and the obtained points. The main objective is to improve the management of long- and short-term recordings by reducing detection errors caused by noise, interference, and artifacts, while also providing the capability for manual results correction. To achieve these objectives, the software uses an SQL Server database, which efficiently manages the data, and detection and delineation algorithms based on the continuous wavelet transform with splines, along with alternatives to optimize processing time. The QRS complex detection algorithm was validated in a previous work with the manually annotated ECG databases: MIT-BIH Arrhythmia, European ST-T, and QT. The QRS detector obtained a Se = 99.91% and a P+ = 99.62% on the first channel of the MIT-BIH, ST-T and QT databases over the 986,930 QRS complexes analyzed. To evaluate the delineation algorithms of the characteristic points of QRS, P and T waves, the QT and PTB databases were used. The mean and standard deviations of the differences between the automatic and manual annotations by CSE experts were calculated. The mean errors range obtained was smaller than one sample (4 ms) to around two samples (8 ms); and the mean standard deviations range was around of two samples (8 ms) to six samples (24 ms).
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-03-31
2025
2025-03-28
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/427242
https://dx.doi.org/10.1088/2057-1976/adb589
url https://hdl.handle.net/2117/427242
https://dx.doi.org/10.1088/2057-1976/adb589
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 4.0 International
http://creativecommons.org/licenses/by/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 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institute of Physics (IOP)
publisher.none.fl_str_mv Institute of Physics (IOP)
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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