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Off-the-person electrocardiography: performance assessment and clinical correlation

dc.contributor.authorSilva, Hugo Plácido da
dc.contributor.authorCarreiras, Carlos
dc.contributor.authorLourenço, André Ribeiro
dc.contributor.authorFred, Ana
dc.contributor.authorNeves, Rui César das
dc.contributor.authorFerreira, Rui
dc.date.accessioned2016-04-27T17:17:23Z
dc.date.available2016-04-27T17:17:23Z
dc.date.issued2015-04-01
dc.description.abstractPrevious work by our group introduced a novel concept and sensor design for “off-the-person” ECG, for which evidence on how it compares against standard clinical-grade equipment has been largely missing. Our objectives with this work are to characterise the off-the-person approach in light of the current ECG systems landscape, and assess how the signals acquired using this simplified setup compare with clinical-grade recordings. Empirical tests have been performed with real-world data collected from a population of 38 control subjects, to analyze the correlation between both approaches. Results show off-the-person data to be correlated with clinical-grade data, demonstrating the viability of this approach to potentially extend preventive medicine practices by enabling the integration of ECG monitoring into multiple dimensions of people’s everyday lives. © 2015, IUPESM and Springer-Verlag Berlin Heidelberg.pt_PT
dc.identifier.citationSILVA, Hugo Plácido da; [et al] - Off-the-person electrocardiography: performance assessment and clinical correlation. Health and Technology. ISSN 2190-7188. Vol. 4, N.º 4 (2015), pp. 309-318pt_PT
dc.identifier.doi10.1007/s12553-015-0098-ypt_PT
dc.identifier.issn2190-7188
dc.identifier.issn2190-7196
dc.identifier.urihttp://hdl.handle.net/10400.21/6105
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Verlagpt_PT
dc.relationLearning from Sequences (LearningS)
dc.subjectElectrocardiographypt_PT
dc.subjectOff-the-personpt_PT
dc.subjectPervasive healthpt_PT
dc.subjectTaxonomypt_PT
dc.titleOff-the-person electrocardiography: performance assessment and clinical correlationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleLearning from Sequences (LearningS)
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/PTDC%2FEEI-SII%2F2312%2F2012/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/SFRH/SFRH%2FBD%2F65248%2F2009/PT
oaire.citation.endPage318pt_PT
oaire.citation.issue4pt_PT
oaire.citation.startPage309pt_PT
oaire.citation.titleHealth and Technologypt_PT
oaire.citation.volume4pt_PT
oaire.fundingStream3599-PPCDT
oaire.fundingStreamSFRH
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isProjectOfPublication48934697-f0f8-4b61-930b-e6ee339e6396
relation.isProjectOfPublicationd7beb08c-39ed-4ac3-8616-b226ef777c17
relation.isProjectOfPublication.latestForDiscovery48934697-f0f8-4b61-930b-e6ee339e6396

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