%0 Conference Proceedings
%T Child or Adult? Inferring Smartphone Users’ Age Group from Touch Measurements Alone
%+ University Stefan cel Mare of Suceava (USU)
%+ University of Florida [Gainesville] (UF)
%+ Bowie State University
%A Vatavu, Radu-Daniel
%A Anthony, Lisa
%A Brown, Quincy
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 15th Human-Computer Interaction (INTERACT)
%C Bamberg, Germany
%3 Human-Computer Interaction – INTERACT 2015
%V LNCS-9299
%N Part IV
%P 1-9
%8 2015-09-14
%D 2015
%R 10.1007/978-3-319-22723-8_1
%K Touch input
%K Children
%K Adults
%K Age group
%K Tap time
%K Offset distance
%K Touch accuracy
%K Classifier
%K Bayes’ rule
%K Touch-screen
%K Smartphone
%K Experiment
%Z Computer Science [cs]Conference papers
%X We present a technique that classifies users’ age group, i.e., child or adult, from touch coordinates captured on touch-screen devices. Our technique delivered 86.5 % accuracy (user-independent) on a dataset of 119 participants (89 children ages 3 to 6) when classifying each touch event one at a time and up to 99 % accuracy when using a window of 7+ consecutive touches. Our results establish that it is possible to reliably classify a smartphone user on the fly as a child or an adult with high accuracy using only basic data about their touches, and will inform new, automatically adaptive interfaces for touch-screen devices.
%G English
%Z TC 13
%2 https://inria.hal.science/hal-01610821/document
%2 https://inria.hal.science/hal-01610821/file/346948_1_En_1_Chapter.pdf
%L hal-01610821
%U https://inria.hal.science/hal-01610821
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC13
%~ IFIP-INTERACT
%~ IFIP-LNCS-9299