GesText: Accelerometer-based Gestural Text-Entry Systems

Eleanor Jones, Jason Alexander, Andreas Andreou, Pourang Irani, Sriram Subramanian, GesText: Accelerometer-based Gestural Text-Entry Systems. Conference on Human Factors in Computing Systems. ISBN 978-1-60558-929-9/10/04. April 2010. PDF, 1108 Kbytes.


Accelerometers are common on many devices, including those required for text-entry. We investigate how to enter text with devices that are solely enabled with accelerometers. The challenge of text-entry with such devices can be overcome by the careful investigation of the human limitations in gestural movements with accelerometers. Preliminary studies provide insight into two potential text-entry designs that purely use accelerometers for gesture recognition. In two experiments, we evaluate the effectiveness of each of the text-entry designs. The first experiment involves novice users over a 45 minute period while the second investigates the possible performance increases over a four day period. Our results reveal that a matrix-based text-entry system with a small set of simple gestures is the most efficient (5.4wpm) and subjectively preferred by participants.

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