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Abstract: Alzheimer´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 obtained.
Congress: International Conference on Ubiquitous Computing and Ambient Intelligence: UCAmI (13th : 2019 : Toledo)
Publisher: MDPI
Year of publication: 2019
No. of pages: 9
Publication type: Conference object
DOI: 10.3390/proceedings2019031072
ISSN: 2504-3900
Publication Url: https://doi.org/10.3390/proceedings2019031072
Consult in UCrea Read publication
SALOMÓN, SERGIO
RAFAEL DUQUE MEDINA
SANTOS BRINGAS TEJERO
JOSE LUIS MONTAÑA ARNAIZ
LAGE, CARMEN
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