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Identification of activities of daily living through data fusion on motion and magnetic sensors embedded on mobile devices

2018Journal article Open access
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dc.contributor.authorPires, Ivan M.
dc.contributor.authorPombo, Nuno
dc.contributor.authorFlórez-Revuelta, Francisco
dc.contributor.authorSpinsante, Susanna
dc.contributor.authorTeixeira, M.C.C.
dc.date.accessioned2024-05-29T10:16:45Z
dc.date.available2024-05-29T10:16:45Z
dc.date.issued2018
dc.description.abstractSeveral types of sensors have been available in off‐the‐shelf mobile devices, including motion, magnetic, vision, acoustic, and location sensors. This paper focuses on the fusion of the data acquired from motion and magnetic sensors, i.e., accelerometer, gyroscope and magnetometer sensors, for the recognition of Activities of Daily Living (ADL). Based on pattern recognition techniques, the system developed in this study includes data acquisition, data processing, data fusion, and classification methods like Artificial Neural Networks (ANN). Multiple settings of the ANN were implemented and evaluated in which the best accuracy obtained, with Deep Neural Networks (DNN), was 89.51%. This novel approach applies L2 regularization and normalization techniques on the sensors’ data proved it suitability and reliability for the ADL recognition.pt_PT
dc.description.sponsorshipThis work was supported by FCT project UID/EEA/50008/2013 (Este trabalho foi suportado pelo projecto FCT UID/EEA/50008/2013). The authors would like to acknowledge the contribution of the COST Action IC1303 – AAPELE – Architectures, Algorithms and Protocols for Enhanced Living Environments.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPIRES, Ivan M. [et al.] (2018) - Identification of activities of daily living through data fusion on motion and magnetic sensors embedded on mobile devices. Pervasive and Mobile Computing. 47, p. 78-93. DOI: https://doi.org/10.1016/j.pmcj.2018.05.005pt_PT
dc.identifier.doihttps://doi.org/10.1016/j.pmcj.2018.05.005pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.11/9011
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectMobile devices sensorspt_PT
dc.subjectSensor data fusionpt_PT
dc.subjectArtificial neural networkspt_PT
dc.subjectIdentification of activities of daily livingpt_PT
dc.titleIdentification of activities of daily living through data fusion on motion and magnetic sensors embedded on mobile devicespt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage93pt_PT
oaire.citation.issue47pt_PT
oaire.citation.startPage78pt_PT
oaire.citation.titlePervasive and Mobile Computingpt_PT
person.familyNameSerrano Pires
person.familyNameGarcia dos Santos
person.familyNameCanavarro Teixeira
person.givenNameIvan Miguel
person.givenNameNuno Manuel
person.givenNameMaria Cristina
person.identifier.ciencia-id211D-8B3D-0131
person.identifier.ciencia-idE719-0DEC-9751
person.identifier.ciencia-id0913-BC21-F66E
person.identifier.orcid0000-0002-3394-6762
person.identifier.orcid0000-0002-3195-3168
person.identifier.orcid0000-0002-8534-9484
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication53c92dfa-27be-4305-9b32-f3cf2e36a4f1
relation.isAuthorOfPublicationc3c2a619-5f2a-42ae-8ee2-f21b9c42a33a
relation.isAuthorOfPublication5c53ae6c-7865-4ef1-adea-ea2fa221aee4
relation.isAuthorOfPublication.latestForDiscovery5c53ae6c-7865-4ef1-adea-ea2fa221aee4

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