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dc.contributor.authorDogan, Hulya
dc.contributor.authorDogan, Ramazan Ozgur
dc.date.accessioned2023-04-13T11:19:29Z
dc.date.available2023-04-13T11:19:29Z
dc.date.issued2023en_US
dc.identifier.citationDogan, Hulya a Send mail to Dogan H.; Dogan, Ramazan Ozgur b Send mail to Dogan R.O. Save all to author list a Department of Software Engineering, Karadeniz Technical University, Trabzon, Turkey b Department of Software Engineering, Gumushane University, Gumushane, Turkeyen_US
dc.identifier.urihttps://link.springer.com/article/10.1007/s11831-023-09916-x
dc.identifier.urihttps://hdl.handle.net/20.500.12440/5909
dc.description.abstractElectrocardiogram (ECG) signal, which is composite of multiple segments such as P-wave, QRS complex and T-wave, plays a crucial role in the treatment of cardiovascular disease. For an analysis of cardiac diagnosis, it is required that clinicians scan the ECG signal for QRS complex or R-peaks (the highest peak of the QRS complex) detection, which relies on their expertise and takes enormous time. In order to provide more realistic treatment of cardiovascular diseases, so many computer-based techniques detecting R-peaks/QRS complex in the ECG signal with noises and different characteristics have been actively developed in research article for many years. Moreover, researchers have created various data sets for R-peaks/QRS complex detection. Although R-peaks/QRS complex detection is one of the notable research areas with so many computer-based techniques and ECG data sets, no comprehensive review paper have been published recently. The main aim of this study is to present a wide range of computer-based techniques proposed for detection of R-peaks/QRS complex. First of all, in this study, computer-based techniques proposed in the literature for the detection of R-peaks/QRS complex and their stages are introduced in detail. The generalization ability of these techniques is investigated deeply. Details are given about the most preferred ECG data sets produced in the literature for the analysis of computer-based techniques. Finally, the performances of computer-based techniques and generalization abilities are analyzed for each data set created in the literature by giving the results of the evaluation metrics. © 2023, The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE).en_US
dc.language.isoengen_US
dc.publisherSpringer Science and Business Media B.V.en_US
dc.relation.ispartofArchives of Computational Methods in Engineeringen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCardiovascular diseaseen_US
dc.subjectComputer aided diagnosisen_US
dc.subjectElectrocardiogram signalen_US
dc.subjectGeneralization abilityen_US
dc.subjectMachine learningen_US
dc.subjectQRS complex detectionen_US
dc.subjectR-peaks detectionen_US
dc.titleA Comprehensive Review of Computer-based Techniques for R-Peaks/QRS Complex Detection in ECG Signalen_US
dc.typearticleen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Yazılım Mühendisliği Bölümüen_US
dc.authorid0000-0001-6415-5755en_US
dc.contributor.institutionauthorDogan, Ramazan Ozgur
dc.identifier.doi10.1007/s11831-023-09916-xen_US
dc.authorwosidGLN-8177-2022en_US
dc.authorscopusid56247021800en_US


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