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Assessing daily activities using a PPG sensor embedded in a wristband-type activity tracker

2020-05-18Comunicação em conferência Acesso restrito
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dc.contributor.authorOliveira, Alexandra
dc.contributor.authorAguiar, Joyce
dc.contributor.authorSilva, Eliana
dc.contributor.authorFaria, Brígida Mónica
dc.contributor.authorGonçalves, Helena
dc.contributor.authorTeófilo, Luís
dc.contributor.authorGonçalves, Joaquim
dc.contributor.authorCarvalho, Victor
dc.contributor.authorCardoso, Henrique Lopes
dc.contributor.authorReis, Luís Paulo
dc.contributor.authorFaria, Brigida Monica
dc.contributor.authorOliveira, Alexandra
dc.date.accessioned2025-10-28T14:35:24Z
dc.date.available2025-10-28T14:35:24Z
dc.date.issued2020-05-18
dc.description.abstractDue to the technological evolution on wearable devices, biosignals, such as inter-cardiac beat interval (RR) time series, are being captured in a noncontrolled environment. These RR signals, derived from photoplethysmography (PPG), enable health status assessment in a more continuous, non-invasive, nonobstructive way, and fully integrated into the individual’s daily activity. However PPG is vulnerable to motion artefacts, which can affect the accuracy of the estimated neurophysiological markers. This paper introduces a method for motion artefact characterization in terms of location and relative variation parameters obtained in different common daily activities. The approach takes into consideration interindividual variability. Data was analyzed throughout related-samples Friedman’s test, followed by pairwise comparison with Wilcoxon signed-rank tests with a Bonferroni correction. Results showed that movement, involving only arms, presents more variability in terms of the two analyzed parameters.por
dc.description.sponsorshipNORTE010247FEDER003446
dc.identifier.citationOliveira, A., Aguiar, J., Silva, E., Faria, B. M., Gonçalves, H., Teófilo, L., Gonçalves, J., Carvalho, V., Cardoso, H. L., & Reis, L. P. (2020). Assessing daily activities using a PPG Sensor embedded in a Wristband-Type Activity Tracker. Em Á. Rocha, H. Adeli, L. P. Reis, S. Costanzo, I. Orovic, & F. Moreira (Eds.), Trends and Innovations in Information Systems and Technologies (WorldCIST 2020) (Vol. 3, pp. 108–119). Springer International Publishing. https://doi.org/10.1007/978-3-030-45697-9_11
dc.identifier.doi10.1007/978-3-030-45697-9_11
dc.identifier.isbn978-3-030-45697-9
dc.identifier.urihttp://hdl.handle.net/10400.22/30685
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relationPEst- UID/CEC/00027/2015; LIACC (FCT/UID/CEC/0027/2020)
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-030-45697-9_11
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectPPG signals
dc.subjectDaily life
dc.subjectHuman activity detection
dc.subjectSensory instrumentation
dc.subjectPhotoplethysmography
dc.subjectMotion artifacts
dc.subjectHeart rate
dc.subjectSensor-based applications
dc.titleAssessing daily activities using a PPG sensor embedded in a wristband-type activity trackerpor
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2020
oaire.citation.conferencePlaceBudva, Montenegro
oaire.citation.endPage119
oaire.citation.issue1161
oaire.citation.startPage108
oaire.citation.volume3
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFaria
person.familyNameOliveira
person.givenNameBrigida Monica
person.givenNameAlexandra
person.identifierR-000-T1F
person.identifier.ciencia-id0D1F-FB5E-55E4
person.identifier.ciencia-id161A-55D9-C256
person.identifier.orcid0000-0003-2102-3407
person.identifier.orcid0000-0001-5872-5504
person.identifier.ridC-6649-2012
person.identifier.scopus-author-id6506476517
person.identifier.scopus-author-id56340903500
relation.isAuthorOfPublication85832a40-7ef9-431a-be0c-78b45ebbae86
relation.isAuthorOfPublicationd6f940a1-3dba-41d2-9a5e-dc1f313eec07
relation.isAuthorOfPublication.latestForDiscovery85832a40-7ef9-431a-be0c-78b45ebbae86

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