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A Convolutional Neural Network-Based Method for Human Movement Patterns Classification in Alzheimer?s Disease

dc.contributor.authorSalomón García, Sergio
dc.contributor.authorDuque Medina, Rafael 
dc.contributor.authorBringas Tejero, Santos 
dc.contributor.authorMontaña Arnaiz, José Luis 
dc.contributor.authorLage, Carmen
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2020-03-04T19:13:06Z
dc.date.available2020-03-04T19:13:06Z
dc.date.issued2019
dc.identifier.issn2504-3900
dc.identifier.urihttp://hdl.handle.net/10902/18337
dc.description.abstractAlzheimer’s disease (AD) constitutes a neurodegenerative pathology that presents mobility disorders as one of its earliest symptoms. Current smartphones integrate accelerometers that can be used to collect mobility data of Alzheimer’s patients. This paper describes a method that processes these accelerometer data and a convolutional neural network (CNN) that classifies the stage of the disease according to the mobility patterns of the patient. The method is applied in a case study with 35 Alzheimer’s patients, in which a classification success rate of 91% was obtainedes_ES
dc.format.extent9 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rights© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license.es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceProceedings 2019, 31(1), 72es_ES
dc.subject.otherMobile and ubiquitous healthes_ES
dc.subject.otherAlzheimeres_ES
dc.subject.otherConvolutional neural networkes_ES
dc.titleA Convolutional Neural Network-Based Method for Human Movement Patterns Classification in Alzheimer?s Diseasees_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.3390/proceedings2019031072es_ES
dc.rights.accessRightsopenAccesses_ES
dc.type.versionacceptedVersiones_ES


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© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license.Excepto si se señala otra cosa, la licencia del ítem se describe como © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license.