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dc.contributor.author
Santillán Cooper, Martín
dc.contributor.author
Armentano, Marcelo Gabriel
dc.date.available
2023-09-21T14:38:04Z
dc.date.issued
2022-11
dc.identifier.citation
Santillán Cooper, Martín; Armentano, Marcelo Gabriel; Predicting future sedentary behaviour using wearable and mobile devices; Pergamon-Elsevier Science Ltd; Information Processing & Management; 59; 6; 11-2022; 1-27
dc.identifier.issn
0306-4573
dc.identifier.uri
http://hdl.handle.net/11336/212497
dc.description.abstract
Sedentarism is a common problem that can affect human health and wellbeing. Predicting sedentary behaviour is an emerging area that can benefit from data collected from sensors available in ubiquitous devices, such as wearables and smartphones. In this paper, we present an approach aiming at predicting the sedentary behaviour of a user from data collected from sensors installed in wearable/mobile devices. We compare personal and impersonal models using a real-life dataset consisting of sensing data of 48 users during 10 weeks. We found that impersonal models using Deep Neural Networks were able to accurately predict the subject's future sedentary behaviour.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights
Atribución-NoComercial-CompartirIgual 2.5 Argentina (CC BY-NC-SA 2.5 AR)
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
MACHINE LEARNING
dc.subject
SEDENTARY BEHAVIOUR PREDICTION
dc.subject
USER MODELLING
dc.subject
WEARABLE AND MOBILE DEVICES
dc.subject.classification
Ciencias de la Computación
dc.subject.classification
Ciencias de la Computación e Información
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
dc.title
Predicting future sedentary behaviour using wearable and mobile devices
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2023-07-07T22:24:54Z
dc.journal.volume
59
dc.journal.number
6
dc.journal.pagination
1-27
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Santillán Cooper, Martín. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas; Argentina
dc.description.fil
Fil: Armentano, Marcelo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
dc.journal.title
Information Processing & Management
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0306457322002059
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.ipm.2022.103104
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