Testing and Analysis of Activities of Daily Living Data with Machine Learning Algorithms

Cufoglu, A. and Coskun, A. 2016. Testing and Analysis of Activities of Daily Living Data with Machine Learning Algorithms. International Journal of Advanced Computer Science & Applications . 7 (3), pp. 436-441. https://doi.org/10.14569/IJACSA.2016.070359

TitleTesting and Analysis of Activities of Daily Living Data with Machine Learning Algorithms
TypeJournal article
AuthorsCufoglu, A.
Coskun, A.
Abstract

It is estimated that 28% of European Union’s population will be aged 65 or older by 2060. Europe is getting older and this has a high impact on the estimated cost to be spent for older people. This is because, compared to the younger generation, older people are more at risk to have/face cognitive impairment, frailty and social exclusion, which could have negative effects on their lives as well as the economy of the European Union. The ‘active and independent ageing’ concept aims to support older people to live active and independent life in their preferred location and this goal can be fully achieved by understanding the older people (i.e their needs, abilities, preferences, difficulties they are facing during the day). One of the most reliable resources for such information is the Activities of Daily Living (ADL), which gives essential information about people’s lives. Understanding this kind of information is an important step towards providing the right support, facilities and care for the older population. In the literature, there is a lack of study that evaluates the performance of Machine Learning algorithms towards understanding the ADL data. This work aims to test and analyze the performance of the well known Machine Learning algorithms with ADL data.

KeywordsActivities of Daily Living; machine learning; Classification Algorithms
JournalInternational Journal of Advanced Computer Science & Applications
Journal citation7 (3), pp. 436-441
ISSN2158-107X
Year2016
PublisherScience and Information Organisation (SAI)
Publisher's version
Digital Object Identifier (DOI)https://doi.org/10.14569/IJACSA.2016.070359
Publication dates
Published01 Mar 2016
LicenseCC BY 4.0

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