Motion Gestures for Mobile Interaction

Recently, sensor hardware has become increasingly pervasive as hardware manufacturers have embedded sensors in mobile phones, media players, game consoles, and laptops. These sensors permit devices to recognize motion gestures&emdash;a gesture performed by physically translating or/and rotating the device. This research explores the use of motion gestures for mobile interaction.

User-Defined Motion Gestures for Mobile Interaction

Jaime Ruiz*, Yang Li**, and Edward Lank*
*University of Waterloo **Google Research

An updated page for this section can be found at http://www.jaimeruiz.com/research/motion_gestures/

Little is known about best-practices in motion gesture design for the mobile computing paradigm. To address this issue, we present the results of a guessability study that elicits end-user motion gestures to invoke commands on a smartphone device. We demonstrate that consensus exists among our participants on parameters of movement and on mappings of motion gestures onto commands. We use this consensus to develop a taxonomy for motion gestures and to specify an end-user inspired motion gesture set. We highlight the implications of this work to the design of smartphone applications and hardware. Finally, we argue that our results influence best practices in design for all gestural interfaces.

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DoubleFlip: A Motion Gesture Delimiter for Mobile Interaction


Jaime Ruiz* and Yang Li**
*University of Waterloo **Google Research

An updated page for this section can be found at http://www.jaimeruiz.com/research/motion_gestures/

To make motion gestures more widely adopted on mobile devices it is important that devices be able to distinguish between motion intended for mobile interaction and every-day motion. In this paper, we present DoubleFlip, a unique motion gesture designed as an input delimiter for mobile motion-based interaction. The DoubleFlip gesture is distinct from regular motion of a mobile device. Based on a collec-tion of 2,100 hours of motion data captured from 99 users, we found that our DoubleFlip recognizer is extremely resistant to false positive conditions, while still achieving a high recognition rate. Since DoubleFlip is easy to perform and unlikely to be accidentally invoked, it provides an always-active input event for mobile interaction.

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