Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/70998
Campo DC Valoridioma
dc.contributor.authorKaushal, Abhisheken_US
dc.contributor.authorYadav, Anjalien_US
dc.contributor.authorDutta, Malay Kishoreen_US
dc.contributor.authorTravieso González, Carlos Manuelen_US
dc.contributor.authorEsteban-Hernández, Luisen_US
dc.date.accessioned2020-03-21T06:05:57Z-
dc.date.available2020-03-21T06:05:57Z-
dc.date.issued2020en_US
dc.identifier.isbn978-1-4503-7630-3en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/70998-
dc.description.abstractCardiovascular diseases are becoming one of the most common causes of mortality all over the world these days. Medical experts and professionals use stethoscope for proper analysis of the cardiac sound. This conventional method required a lot of and also involve medical experts. This paper presents a low cost, portable device which can automatically classified the heart condition by recording the heart sound of the patient. The device is developed in such a way that a non-medical person can use it for the purpose of initial screening of the heart condition of the patients. The proposed device is based on supervised classifier which help in identifying a recorded heart sound either as normal or abnormal heart sound. Supervised classification model is developed on the basis of discriminatory features that are extracted using cepstrum analysis of the heart sound. The proposed method has achieved an accuracy of 97% in correctly classifying a heart sound PCG signal as normal and abnormal. This make the developed device to use in dispensary for the initial screening of the patients.en_US
dc.languageengen_US
dc.publisherAssociation for Computing Machineryen_US
dc.sourceAPPIS 2020: 3rd International Conference on Applications of Intelligent Systems, Las Palmas de Gran Canaria, January, 2020, article 17en_US
dc.subject320501 Cardiologíaen_US
dc.subject3314 Tecnología médicaen_US
dc.subject.otherCardiac Sounden_US
dc.subject.otherDiagnostic Deviceen_US
dc.subject.otherLow Costen_US
dc.subject.otherPcg Recordingen_US
dc.subject.otherPortableen_US
dc.subject.otherSvmen_US
dc.titleLow Cost Portable Diagnostic Device for Automatic Classification of the Abnormal Cardiac Sound using PGC Recordingen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conferenceInternational Conference on Applications of Intelligent Systems (APPIS 2020)en_US
dc.identifier.doi10.1145/3378184.3378213en_US
dc.identifier.scopus85081083255-
dc.contributor.authorscopusid57215532994-
dc.contributor.authorscopusid57195513394-
dc.contributor.authorscopusid35291803600-
dc.contributor.authorscopusid57201316633-
dc.contributor.authorscopusid57215532908-
dc.investigacionCiencias de la Saluden_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.identifier.conferenceidevents121681-
dc.identifier.ulpgces
dc.contributor.buulpgcBU-TELen_US
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-4621-2768-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameTravieso González, Carlos Manuel-
crisitem.event.eventsstartdate07-01-2020-
crisitem.event.eventsenddate09-01-2020-
Colección:Actas de congresos
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