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.
CITATION STYLE
Vatavu, R. D., Anthony, L., & Brown, Q. (2015). Child or adult? Inferring Smartphone users’ age group from touch measurements alone. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9299, pp. 1–9). Springer Verlag. https://doi.org/10.1007/978-3-319-22723-8_1
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