GesText: Accelerometer-Based Gestural Text-Entry Systems

Eleanor Jones, Jason Alexander, Andreas Andreou, Pourang Irani, Sriram Subramanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

65 Citations (Scopus)
2 Downloads (Pure)

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the 28th International Conference on Human Factors in Computing Systems (CHI'10)
PublisherAssociation for Computing Machinery
Pages2173-2182
Number of pages10
ISBN (Print)978-1-60558-929-9
DOIs
Publication statusPublished - 10 Apr 2010

Publication series

NameCHI '10
PublisherACM

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