A Model for Detecting and Locating Behaviour Changes in Mobile Touch Targeting Sequences

Human Pose & Activity RecognitionMotor Impairment Assistive Input Technologies

Touch offset models capture users' targeting behaviour patterns across the screen. We present and evaluate the first extension of these models to explicitly address behaviour changes. We focus on user changes in particular: Given only a series of touch/target locations (x, y), our model detects 1) if the user has changed therein, and if so, 2) at which touch. We evaluate our model on smartphone targeting and typing data from the lab (N=28) and field (N=30). The results show that our model can exploit touch targeting sequences to reveal user changes. Our model outperforms existing non-sequence touch offset models and does not require training data. We discuss the model's limitations and ideas for further improvement. We conclude with recommendations for its integration into future touch biometric systems.

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https://hci.top/en/papers/iui/8033/2018

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IUI
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2018
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Human Pose & Activity Recognition, Motor Impairment Assistive Input Technologies
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