Repository logo
 
Publication

Heart disease detection using ECG lead I and multiple pattern recognition classifiers

dc.contributor.authorPereira, Renato
dc.contributor.authorBispo, Bruno
dc.contributor.authorRodrigues, Pedro Miguel
dc.date.accessioned2021-05-11T10:28:23Z
dc.date.available2021-05-11T10:28:23Z
dc.date.issued2020-04-04
dc.description.abstractECG is an important tool to assist in heart diseases diagnosis. The works found in the literature have the common goal of discriminating between binary study groups, one pathological and one control, even when ECG records from patients diagnosed with several pathologies are available in the databases. This work proposes a method to detect ECG morphological features and to analyze the capacity of this ECG features to discriminate 28 pairs of study groups, combining 7 pathological groups and 1 control group, presented in the PTB Diagnostic ECG Database. For each pair, it was achieved an accuracy between 77.4% and 100%, with an average of 94%, using several pattern recognition classifiers.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.eissn2250-3021
dc.identifier.issn2278-8719
dc.identifier.urihttp://hdl.handle.net/10400.14/32993
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectHeart diseasespt_PT
dc.subjectECG featurespt_PT
dc.subjectPattern recognitionpt_PT
dc.subjectPTB Diagnostic ECG databasespt_PT
dc.subjectClassifierspt_PT
dc.titleHeart disease detection using ECG lead I and multiple pattern recognition classifierspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage8pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleIOSR Journal of Engineeringpt_PT
oaire.citation.volume10pt_PT
person.familyNameRodrigues
person.givenNamePedro Miguel
person.identifier1944552
person.identifier.ciencia-id7416-BD33-8299
person.identifier.orcid0000-0002-5381-6615
person.identifier.scopus-author-id57551233700
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication084419ea-3a19-4216-bae7-db55d4786eab
relation.isAuthorOfPublication.latestForDiscovery084419ea-3a19-4216-bae7-db55d4786eab

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
28390869.pdf
Size:
662.61 KB
Format:
Adobe Portable Document Format