Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/107997
DC FieldValueLanguage
dc.contributor.authorGordalina, Gonçalo-
dc.contributor.authorFigueiredo, João-
dc.contributor.authorMartinho, Ricardo-
dc.contributor.authorRijo, Rui-
dc.contributor.authorCorreia, Pedro-
dc.contributor.authorAssunção, Pedro-
dc.contributor.authorSeco, Alexandra-
dc.contributor.authorPires, Gabriel-
dc.contributor.authorOliveira, Luís-
dc.contributor.authorFonseca-Pinto, Rui-
dc.date.accessioned2023-08-04T08:31:16Z-
dc.date.available2023-08-04T08:31:16Z-
dc.date.issued2018-
dc.identifier.issn18770509pt
dc.identifier.urihttps://hdl.handle.net/10316/107997-
dc.description.abstractAccording to estimates by the World Health Organization, the average life expectancy will continue to rise. This indicator, being a measure of success in terms of healthcare, is not synonymous with quality of life and will increase healthcare costs. Associated with this problem are also the changes in terms of the organization of society, which has not been able to solve these constraints of functional limitations, dementia, social isolation, and loneliness. This paper presents the concept of adaptive surveillance based on mobile technology and artificial intelligence, presented in the context of a global physical activity monitoring program (MOVIDA), in his domus dimension designed to the elderly people with some functional limitation or dementia. The proposed solution for an adaptive surveillance is thus to conduct direct supervision programs, to enroll persons who live alone or in nursing homes who need supervision without limiting their individual autonomy. The preliminary results show that it is possible to use the data obtained from a mobile smartphone to identify routines and use this information to identify daily patterns. Changes to these routine patterns can be used to generate alarms for caregivers.pt
dc.language.isoengpt
dc.publisherElsevierpt
dc.relationFCT - MOVIDA project: 02/SAICT/2016 – 23878pt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt
dc.subjectMobile Healthpt
dc.subjecteHealthpt
dc.subjectArtifical Intelligencept
dc.subjectAdaptive Surveillancept
dc.titleTracking human routines towards adaptive monitoring: the MOVIDA.domus platformpt
dc.typearticle-
degois.publication.firstPage41pt
degois.publication.lastPage48pt
degois.publication.titleProcedia Computer Sciencept
dc.peerreviewedyespt
dc.identifier.doi10.1016/j.procs.2018.10.007pt
degois.publication.volume138pt
dc.date.embargo2018-01-01*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextCom Texto completo-
crisitem.author.researchunitINESC Coimbra – Institute for Systems Engineering and Computers at Coimbra-
crisitem.author.researchunitISR - Institute of Systems and Robotics-
crisitem.author.parentresearchunitUniversity of Coimbra-
crisitem.author.orcid0000-0003-1157-7510-
crisitem.author.orcid0000-0001-9967-845X-
Appears in Collections:I&D INESCC - Artigos em Revistas Internacionais
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This item is licensed under a Creative Commons License Creative Commons