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GesText: Accelerometer-Based Gestural Text-Entry Systems

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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http://dx.doi.org/10.1145/1753326.1753655

Eleanor Jones, Jason Alexander, Andreas Andreou, Pourang Irani and Sriram Subramanian. 2010. GesText: Accelerometer-Based Gestural Text-Entry Systems. In Proceedings of the 28th international conference on Human factors in computing systems (CHI '10). Atlanta, Georgia, USA. ACM, 2173-2182.

Bibtext Entry

@INPROCEEDINGS { Jones10,
    AUTHOR = { Eleanor Jones and Jason Alexander and Andreas Andreou and Pourang Irani and Sriram Subramanian },
    TITLE = { GesText: Accelerometer-Based Gestural Text-Entry Systems },
    BOOKTITLE = { Proceedings of the 28th international conference on Human factors in computing systems (CHI '10) },
    YEAR = { 2010 },
    PAGES = { 2173--2182 },
    DOI = { 10.1145/1753326.1753655 },
    PUBLISHER = { ACM },
    ADDRESS = { Atlanta, Georgia, USA },
}

Authors

Pourang Irani

Pourang Irani

Professor
Canada Research Chair

As well as: , Eleanor Jones, Jason Alexander, Andreas Andreou and Sriram Subramanian