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Recognition of human activity based on sparse data collected from smartphone sensors

2019-02-23Conference object Open access
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dc.contributor.authorFigueiredo, João
dc.contributor.authorGordalina, Gonçalo
dc.contributor.authorFrazão Correia, Pedro
dc.contributor.authorPires, Gabriel
dc.contributor.authorLopes de Oliveira, Luís Miguel
dc.contributor.authorMartinho, Ricardo
dc.contributor.authorRijo, Rui
dc.contributor.authorAssunção, Pedro
dc.contributor.authorSeco, Alexandra
dc.contributor.authorFonseca-Pinto, Rui
dc.date.accessioned2021-07-17T00:01:58Z
dc.date.available2021-07-17T00:01:58Z
dc.date.issued2019-02-23
dc.description.abstractThis paper proposes a method of human activity monitoring based on the regular use of sparse acceleration data and GPS positioning collected during smartphone daily utilization. The application addresses, in particular, the elderly population with regular activity patterns associated with daily routines. The approach is based on the clustering of acceleration and GPS data to characterize the user's pattern activity and localization for a given period. The current activity pattern is compared to the one obtained by the learned data patterns, generating alarms of abnormal activity and unusual location. The obtained results allow to consider that the usage of the proposed method in real environments can be beneficial for activity monitoring without using complex sensor networks.pt_PT
dc.description.sponsorshipThis work has been financially supported by the IC&DT Project MOVIDA: SAICT-POL/23878/2016 | CENTRO-01-0145-FEDER-023878 and Project VITASENIOR-MT: SAICT-POL/23659/2016 | CENTRO-01-0145-FEDER-023659 with FEDER funding through programs CENTRO2020 and FCT.pt_PT
dc.description.sponsorshipCENTRO-01-0145-FEDER-023878
dc.description.sponsorshipCENTRO-01-0145-FEDER-023659
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/ENBENG.2019.8692447pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/37107
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherIEEEpt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8692447pt_PT
dc.subjectsparse datapt_PT
dc.subjectsmartphone sensorspt_PT
dc.subjecthuman activity monitoringpt_PT
dc.subjectsparse acceleration datapt_PT
dc.subjectGPS positioningpt_PT
dc.subjectelderly populationpt_PT
dc.subjectlearned data patternspt_PT
dc.subjectlocalizationpt_PT
dc.titleRecognition of human activity based on sparse data collected from smartphone sensorspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceLisbon, Portugalpt_PT
oaire.citation.endPage4pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title2019 IEEE 6th Portuguese Meeting on Bioengineering (ENBENG)pt_PT
person.familyNameFrazão Correia
person.familyNamePires
person.familyNameLopes de Oliveira
person.givenNamePedro
person.givenNameGabriel
person.givenNameLuís Miguel
person.identifierhttps://scholar.google.com/citations?user=84oroekAAAAJ&hl=en
person.identifier.ciencia-id5211-FE18-4490
person.identifier.ciencia-id9C19-9DF1-EB2B
person.identifier.ciencia-idC512-647A-38F1
person.identifier.orcid0000-0001-9451-136X
person.identifier.orcid0000-0001-9967-845X
person.identifier.orcid0000-0001-9412-5012
person.identifier.scopus-author-id55399236400
person.identifier.scopus-author-id6701432446
person.identifier.scopus-author-id37065109600
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationb873efa8-6ce1-4dce-b8be-e370f55cca2f
relation.isAuthorOfPublication049f8c38-bea3-414e-9de5-b45ae8b90ad7
relation.isAuthorOfPublication4f447232-c9be-485e-be78-8cbded1a3e40
relation.isAuthorOfPublication.latestForDiscovery049f8c38-bea3-414e-9de5-b45ae8b90ad7

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