Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48802
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dc.contributor.authorSingh, Anushikhaen_US
dc.contributor.authorDutta, Malay Kishoreen_US
dc.contributor.authorTravieso, Carlos M.en_US
dc.date.accessioned2018-11-24T01:03:42Z-
dc.date.available2018-11-24T01:03:42Z-
dc.date.issued2017en_US
dc.identifier.isbn9781538608500en_US
dc.identifier.urihttp://hdl.handle.net/10553/48802-
dc.description.abstractBody auscultation one of the main common clinical diagnostic technique for assessment of cardiac disorders. This clinical method is cheap and effective and requires professional doctors to understand and interpret the heart sound for diagnosis of cardiac diseases. This paper presents basic analysis and comparison of heart sounds recorded from healthy and unhealthy subjects for automated screening of cardiac disorders. Some characteristics of heart sounds such as probability distribution of amplitude and frequency contents are quantified using signal processing to automate the diagnosis of cardiac disorders. Experiments were carried on the Heart sounds database created under National Institute of Health (National Center for Research Resources) and results are encouraging. The experiment results indicates enough discrimination between heart sounds from healthy and unhealthy heart sounds for automated screening of cardiac disorders using signal processing.en_US
dc.languageengen_US
dc.relation.ispartof2017 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, IWOBI 2017 - Proceedingsen_US
dc.source2017 International Work Conference on Bio-Inspired Intelligence: Intelligent Systems for Biodiversity Conservation, IWOBI 2017 - Proceedings (7985528)en_US
dc.subject3314 Tecnología médicaen_US
dc.subject.otherCardiac Disordersen_US
dc.subject.otherHeartSoundsen_US
dc.subject.otherBody auscultationen_US
dc.subject.otherSignal processingen_US
dc.titleAnalysis of Heart Sound for Automated Diagnosis of Cardiac Disordersen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference5th IEEE International Work Conference on Bio-Inspired Intelligence, IWOBI 2017en_US
dc.identifier.doi10.1109/IWOBI.2017.7985528en_US
dc.identifier.scopus85028528115-
dc.contributor.authorscopusid55885045200-
dc.contributor.authorscopusid35291803600-
dc.contributor.authorscopusid6602376272-
dc.identifier.issue7985528-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.date.coverdateJulio 2017en_US
dc.identifier.conferenceidevents121608-
dc.identifier.ulpgces
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.eventsstartdate10-07-2017-
crisitem.event.eventsenddate12-07-2017-
Appears in Collections:Actas de congresos
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