A New Method for Classification of ECG Arrhythmias Using Neural Network with Adaptive Activation Function

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dc.contributor.authorÖzbay, Yüksel
dc.contributor.authorTezel, Gülay
dc.date.accessioned2020-03-26T17:46:44Z
dc.date.available2020-03-26T17:46:44Z
dc.date.issued2010
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this study, new neural network models with adaptive activation function (NNAAF) were implemented to classify ECG arrhythmias. Our NNAAF models included three types named as NNAAF-1, NNAAF-2 and NNAAf-3. Activation functions with adjustable free parameters were used in hidden neurons of these models to improve classical MLP network. In addition, these three NNAAF models were compared with the MLP model implemented in similar conditions. Ten different types of ECG arrhythmias were selected from MIT-BIH ECG Arrhythmias Database to train NNAAFs and MLP models. Moreover, all models tested by the ECG signals of 92 patients (40 males and 52 females, average age is 39.75 +/- 19.06). The average accuracy rate of all models in the training processing was found as 99.92%. The average accuracy rate of the all models in the test phases was obtained as 98.19.en_US
dc.description.sponsorshipCoordinatorship of Selcuk UniversitySelcuk Universityen_US
dc.description.sponsorshipThis work is supported by the Coordinatorship of Selcuk University's Scientific Research Projects.en_US
dc.identifier.citationÖzbay, Y., Tezel, G., (2010). A New Method for Classification of ECG Arrhythmias Using Neural Network with Adaptive Activation Function. Digital Signal Processing, 20(4), 1040-1049. Doi: 10.1016/j.dsp.2009.10.016
dc.identifier.doi10.1016/j.dsp.2009.10.016en_US
dc.identifier.endpage1049en_US
dc.identifier.issn1051-2004en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1040en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.dsp.2009.10.016
dc.identifier.urihttps://hdl.handle.net/20.500.12395/24530
dc.identifier.volume20en_US
dc.identifier.wosWOS:000278687400008en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorÖzbay, Yüksel
dc.institutionauthorTezel, Gülay
dc.language.isoenen_US
dc.publisherAcademic Press Inc Elsevier Scienceen_US
dc.relation.ispartofDigital Signal Processingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectAdaptive neural networken_US
dc.subjectAdaptive activation functionen_US
dc.subjectMlpen_US
dc.subjectClassificationen_US
dc.subjectEcgen_US
dc.subjectArrhythmiaen_US
dc.titleA New Method for Classification of ECG Arrhythmias Using Neural Network with Adaptive Activation Functionen_US
dc.typeArticleen_US

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