Child or Adult? Inferring Smartphone Users’ Age Group from Touch Measurements Alone

  • Radu-Daniel Vatavu
  • Lisa Anthony
  • Quincy Brown
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9299)


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.


Touch input Children Adults Age group Tap time Offset distance Touch accuracy Classifier Bayes’ rule Touch-screen Smartphone Experiment 



This work was supported by the project MappingBooks, no. PN-II-PT-PCCA-2013-4-1878, 4/01.07.2014, funded by UEFISCDI, Romania.


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Copyright information

© IFIP International Federation for Information Processing 2015

Authors and Affiliations

  • Radu-Daniel Vatavu
    • 1
  • Lisa Anthony
    • 2
  • Quincy Brown
    • 3
  1. 1.University Stefan cel Mare of SuceavaSuceavaRomania
  2. 2.Department of CISEUniversity of FloridaGainesvilleUSA
  3. 3.Bowie State UniversityBowieUSA

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