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User-Age Classification Using Touch Gestures on Smartphones

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dc.contributor.author AL-Showarah, Suleyman
dc.contributor.author AL-Jawad, Naseer
dc.contributor.author Sellahewa, Harin
dc.date.accessioned 2016-10-26T05:07:23Z
dc.date.available 2016-10-26T05:07:23Z
dc.date.issued 2016-10-26T05:07:23Z
dc.identifier.citation AL-Showarah, S., AL-Jawad, N., & Sellahewa, H. (2015). User-Age Classification Using Touch Gestures on Smartphones. International Journal of Multidisciplinary Studies (IJMS), 2(1), 97-109.
dc.identifier.issn 23620797
dc.identifier.uri http://dr.lib.sjp.ac.lk/handle/123456789/3329
dc.description.abstract In this paper we investigated the possibility of classifying users’ age-group using gesture-based features on smartphones. The features used were gesture accuracy, speed, movement time, and finger/force pressure. Nearest Neighbour classification was used to classify a given user’s age-group. The 50 participants involved in this research included 25 elderly and 25 younger users. User-dependent and user-independent age-group classification scenarios were considered. On each scenario, two types of analysis were considered; using a single-feature and combined-features to represent a user-age group. The results revealed that classification accuracy was relatively higher for the younger age group than the elderly age group. Also, a higher classification accuracy was achieved on the small smartphone than on mini-tablets. The results also showed that the classification accuracy increases when combining the gesture features in to a single representation as opposed to using a single gesture feature. en_US
dc.language.iso en en_US
dc.subject User’s age-group classification en_US
dc.subject security en_US
dc.subject finger on touchscreen en_US
dc.title User-Age Classification Using Touch Gestures on Smartphones en_US
dc.type Article en_US
dc.date.published 2015

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