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Smartphone-based Transport Mode Detection for Elderly Care

dc.contributor.authorCardoso, Nuno
dc.contributor.authorMadureira, João
dc.contributor.authorPereira, Nuno
dc.date.accessioned2017-07-14T09:44:45Z
dc.date.embargo2117
dc.date.issued2016
dc.description.abstractSmartphones are everywhere, and they are a very attractive platform to perform unobtrusive monitoring of users. In this work, we use common features of modern smartphones to build a human activity recognition (HAR) system for elderly care. We have built a classifier that detects the transport mode of the user including whether an individual is inactive, walking, in bus, in car, in train or in metro. We evaluated our approach using over 24 hours of transportation data from a group of 15 individuals. Our tests show that our classifier can detect the transportation mode with over 90% accuracy.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/HealthCom.2016.7749465pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/10069
dc.language.isoengpt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.ispartofseriesHealthcom;2016
dc.relation.publisherversionhttp://ieeexplore.ieee.org/document/7749465/pt_PT
dc.subjectInertial Sensorspt_PT
dc.subjectAccelerometerpt_PT
dc.subjectClassification Algorithmspt_PT
dc.subjectTransport Detectionpt_PT
dc.subjectSmartphonespt_PT
dc.titleSmartphone-based Transport Mode Detection for Elderly Carept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.title18th International Conference on e-Health Networking, Applications and Servicespt_PT
person.familyNamePereira
person.givenNameNuno
person.identifier.ciencia-id7818-7C77-02BA
person.identifier.orcid0000-0001-6370-9373
person.identifier.scopus-author-id8404645300
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication33fee0a6-53b7-45d5-9be3-f48b1c7064d1
relation.isAuthorOfPublication.latestForDiscovery33fee0a6-53b7-45d5-9be3-f48b1c7064d1

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