Mohammad Faizuddin Mohd Noor

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We demonstrate that front-of-screen targeting on mobile phones can be predicted from back-of-device grip manipulations. Using simple, low-resolution capacitive touch sensors placed around a standard phone, we outline a machine learning approach to modelling the grip modulation and inferring front-of-screen touch targets. We experimentally demonstrate that(More)
We show that when users make errors on mobile devices they make immediate and distinct physical responses that can be observed with standard sensors. We used three standard cognitive tasks (Flanker, Stroop and SART) to induce errors from 20 participants. Using simple low-resolution capacitive touch sensors placed around a standard mobile device and the(More)
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