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dc.creatorBenini, Sergio
dc.creatorIvanović, Marija D.
dc.creatorSavardi, Mattia
dc.creatorKršić, Jelena
dc.creatorHadžievski, Ljupčo
dc.creatorBaronio, Fabio
dc.date.accessioned2021-09-08T11:49:35Z
dc.date.available2021-09-08T11:49:35Z
dc.date.issued2021
dc.identifier.issn2352-3409
dc.identifier.urihttps://vinar.vin.bg.ac.rs/handle/123456789/9547
dc.description.abstractThe provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 min of post-shock waveform. Patients’ ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation to different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation. © 2020en
dc.language.isoen
dc.relationinfo:eu-repo/grantAgreement/EC/H2020/691051/EU//
dc.relationinfo:eu-repo/grantAgreement/MESTD/Integrated and Interdisciplinary Research (IIR or III)/45010/RS//
dc.relation.isreferencedbyhttps://doi.org/10.1016/j.artmed.2020.101963
dc.relation.isreferencedbyhttps://doi.org/10.17632/wpr5nzyn2z.1
dc.relation.isreferencedbyhttps://vinar.vin.bg.ac.rs/handle/123456789/9549
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceData in Brief
dc.subjectcardiac arresten
dc.subjectDefibrillationen
dc.subjectECGen
dc.subjectPredictionen
dc.subjectresuscitationen
dc.subjectShock outcomeen
dc.subjectVentricular fibrillation (VF)en
dc.subjectwaveformen
dc.titleECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patientsen
dc.typearticleen
dc.rights.licenseBY-NC-ND
dcterms.abstractСаварди, Маттиа; Кршић, Јелена; Бенини, Сергио; Ивановић, Марија Д.; Хаджиевски, Љупчо; Баронио, Фабио;
dc.rights.holder© 2020 Published by Elsevier Inc.
dc.citation.volume34
dc.citation.spage106635
dc.identifier.wos000617525400025
dc.identifier.doi10.1016/j.dib.2020.106635
dc.identifier.pmid33364270
dc.type.versionpublishedVersion
dc.identifier.scopus2-s2.0-85099497948
dc.identifier.fulltexthttps://vinar.vin.bg.ac.rs/bitstream/id/24374/1-s2.0-S0933365720312288-main.pdf


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