Article ID Journal Published Year Pages File Type
534196 Pattern Recognition Letters 2015 7 Pages PDF
Abstract

•The information content of touchscreen gestures are analyzed.•Besides user identity, gender and touchscreen experience level of the user can be revealed from gestures.•Sequences of 10 strokes are appropriate for high accuracy user identity, gender and touchscreen experience level recognition.

The aim of this study is to analyze information that can be revealed from simple touch gestures such as horizontal and vertical scrolling. Touch gestures contain identity information, they can reflect the user’s experience using touchscreen and they can infer the gender of the user. The statements are based on measurements on a large touch dataset collected from 71 users using 8 different mobile devices, both tablets and phones. Touch data were divided in strokes and classification measurements were investigated based on single and multiple strokes. Classification results based on single stroke are inaccurate, which can be improved by using multiple strokes. Measurements prove that identity, gender and user’s touchscreen experience level can be accurately predicted from a sequence of 10 strokes. In addition to the different classification results we present statistical analysis of the collected data in order to reveal basic differences between male and female users as well as for less and more experienced touchscreen users.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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