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dc.contributor.authorAyala Fernández, Unai
dc.contributor.authorIrusta Zarandona, Unai ORCID
dc.contributor.authorRuiz Ojeda, Jesús María
dc.contributor.authorEftestol, T.
dc.contributor.authorKramer-Johansen, J.
dc.contributor.authorAlonso-Atienza, F.
dc.contributor.authorAlonso Ruiz de Erenchun, Estibaliz ORCID
dc.contributor.authorGonzález Otero, Digna María ORCID
dc.date.accessioned2016-04-01T13:32:52Z
dc.date.available2016-04-01T13:32:52Z
dc.date.issued2014
dc.identifier.citationBioMed Research International 2014 : (2014) // Article ID 872470es
dc.identifier.issn2314-6133
dc.identifier.issn2314-6141
dc.identifier.urihttp://hdl.handle.net/10810/17752
dc.description.abstractnterruptions in cardiopulmonary resuscitation (CPR) compromise defibrillation success. However, CPR must be interrupted to analyze the rhythm because although current methods for rhythm analysis during CPR have high sensitivity for shockable rhythms, the specificity for nonshockable rhythms is still too low. This paper introduces a new approach to rhythm analysis during CPR that combines two strategies: a state-of-the-art CPR artifact suppression filter and a shock advice algorithm (SAA) designed to optimally classify the filtered signal. Emphasis is on designing an algorithm with high specificity. The SAA includes a detector for low electrical activity rhythms to increase the specificity, and a shock/no-shock decision algorithm based on a support vector machine classifier using slope and frequency features. For this study, 1185 shockable and 6482 nonshockable 9-s segments corrupted by CPR artifacts were obtained from 247 patients suffering out-of-hospital cardiac arrest. The segments were split into a training and a test set. For the test set, the sensitivity and specificity for rhythm analysis during CPR were 91.0% and 96.6%, respectively. This new approach shows an important increase in specificity without compromising the sensitivity when compared to previous studies.es
dc.description.sponsorshipThis work received financial support from Spanish Ministerio de Economia y Competitividad (Projects TEC2012-31144 and TEC2012-31928), from the UPV/EHU (unit UFI11/16), and from the Basque government (Grants BFI-2010-174, BFI2010-235, and BFI-2011-166). The authors would like to thank Professor Rojo-A lvarez from the University Rey Juan Carlos (Madrid, Spain) for his assistance with SVM classifiers and for his thorough review of the paper.es
dc.language.isoenges
dc.publisherHindawi Publishinges
dc.relationinfo:eu-repo/grantAgreement/MINECO/TEC2012-31144
dc.relationinfo:eu-repo/grantAgreement/MINECO/TEC2012-31928
dc.rightsinfo:eu-repo/semantics/openAccesses
dc.subjecthospital cardiac-arrestes
dc.subjectamerican-heart-associationes
dc.subjectautomated external defibrillatorses
dc.subjecthealth-care professionalses
dc.subjectsupport vector machineses
dc.subjectchest compression ratees
dc.subjectventricular fibrillationes
dc.subjectCPR artifactses
dc.subjectlife-supportes
dc.subjecthuman ECGes
dc.titleA Reliable Method for Rhythm Analysis during Cardiopulmonary Resuscitationes
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder© 2014 U. Ayala et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.es
dc.relation.publisherversionhttp://www.hindawi.com/journals/bmri/2014/872470/abs/es
dc.identifier.doi10.1155/2014/872470
dc.departamentoesIngeniería de comunicacioneses_ES
dc.departamentoeuKomunikazioen ingeniaritzaes_ES


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