Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/22274
DC FieldValueLanguage
dc.contributor.authorPires, Ivan Miguelen_US
dc.contributor.authorMarques, Gonçaloen_US
dc.contributor.authorGarcia, Nuno Men_US
dc.contributor.authorZdravevski, Eftimen_US
dc.date.accessioned2022-08-15T09:57:11Z-
dc.date.available2022-08-15T09:57:11Z-
dc.date.issued2020-01-01-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/22274-
dc.description.abstractThe accelerometer is available on most of these mobile devices. It allows the acquisition and calculation of different physical parameters. Due to the use of pattern recognition, it also enables the identification of several Activities of Daily Living (ADL), such as walking, running, going downstairs, going upstairs, and standing. The feature extraction step performs the extraction of the five most significant distances between peaks, the average, standard deviation, variance and median of extracted peaks and raw data, and the maximum and minimum of raw data. The focus of this paper is the implementation of multiple artificial intelligence methods for the recognition of ADL, including Logistic Regression, Combined nomenclature rule inducer, Neural Network, Naive Bayes, Support Vector Machine, Decision Tree, Stochastic Gradient Descent, and k-Nearest Neighbor.en_US
dc.publisherElsevieren_US
dc.relation.ispartofProcedia Computer Scienceen_US
dc.titleIdentification of Activities of Daily Living through Artificial Intelligence: an accelerometry-based approachen_US
dc.typeJournal Articleen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles
Files in This Item:
File Description SizeFormat 
1-s2.0-S1877050920317245-main.pdf627.9 kBAdobe PDFView/Open
Show simple item record

Page view(s)

50
checked on May 2, 2025

Download(s)

11
checked on May 2, 2025

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.