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PhysioLab - a multivariate physiological computing toolbox for ECG, EMG and EDA signals: a case of study of cardiorespiratory fitness assessment in the elderly population

2017Journal article Restricted access
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dc.contributor.authorMuñoz, John Edison
dc.contributor.authorGouveia, Elvio Rubio
dc.contributor.authorCameirão, Mónica S.
dc.contributor.authorBermúdez i Badia, Sergi
dc.date.accessioned2018-12-13T15:39:22Z
dc.date.available2018-12-13T15:39:22Z
dc.date.issued2017
dc.description.abstractThe exponential increase of wearable health-tracking technologies offers new possibilities but also poses new challenges in signal processing to enable fitness monitoring through multimodal physiological recordings. Although there are several software tools used for postprocessing in physiological computing applications, limitations in the analysis, incorporating signals from multiple sources, integrating contextual information and providing information visualization tools prevent a widespread use of this technology. To address these issues, we introduce PhysioLab, a multimodal processing Matlab tool for the data analysis of Electromyography (EMG), Electrocardiography (ECG) and Electrodermal Activity (EDA). The software is intendedtofacilitatetheprocessingandcomprehensionofmultimodalphysiologicaldatawiththe aim of assessing fitness in several domains. A unique feature of PhysioLab is that is informed by normative data grouped by age and sex, allowing contextualization of data based on users’ demographics. Besides signal processing, PhysioLab includes a novel approach to multivariablept_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1007/s11042-017-5069-zpt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/2201
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Verlagpt_PT
dc.relationAHA: Augmented Human Assistance
dc.subjectCardiorespiratory fitness assessmentpt_PT
dc.subjectElderly populationpt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Sociaispt_PT
dc.titlePhysioLab - a multivariate physiological computing toolbox for ECG, EMG and EDA signals: a case of study of cardiorespiratory fitness assessment in the elderly populationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleAHA: Augmented Human Assistance
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5665-PICT/CMUP-ERI%2FHCI%2F0046%2F2013/PT
oaire.citation.endPage11546pt_PT
oaire.citation.startPage11521pt_PT
oaire.citation.titleMultimedia Tools and Applicationspt_PT
oaire.citation.volume77(9)pt_PT
oaire.fundingStream5665-PICT
person.familyNameGouveia
person.familyNameCameirão
person.familyNameBermúdez i Badia
person.givenNameÉlvio Rúbio
person.givenNameMónica
person.givenNameSergi
person.identifier239789
person.identifier.ciencia-id3B10-8BDF-0D67
person.identifier.ciencia-id0A12-4F21-0CC2
person.identifier.ciencia-idCA17-5E88-2B37
person.identifier.orcid0000-0003-0927-692X
person.identifier.orcid0000-0002-5352-0128
person.identifier.orcid0000-0003-4452-0414
person.identifier.ridC-8675-2018
person.identifier.ridC-8681-2018
person.identifier.scopus-author-id21740694600
person.identifier.scopus-author-id6506360007
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication644f9f6a-81be-4b72-9ded-6eb1b8e251f4
relation.isAuthorOfPublicationef8f1e3b-3c09-4817-80d0-d96aa88051a2
relation.isAuthorOfPublication.latestForDiscoverybac4d787-0647-4e23-82d0-0a905ddcd3e1
relation.isProjectOfPublication15913ce4-5392-4ce6-ab2f-1b155da9c18d
relation.isProjectOfPublication.latestForDiscovery15913ce4-5392-4ce6-ab2f-1b155da9c18d

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