GesText: Accelerometer-based Gestural Text-Entry Systems

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

Research output: Contribution to journalArticle (Academic Journal)peer-review

68 Citations (Scopus)

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.
Translated title of the contributionGesText: Accelerometer-based Gestural Text-Entry Systems
Original languageEnglish
Pages (from-to)-
JournalConference on Human Factors in Computing Systems
Publication statusPublished - 2010

Bibliographical note

ISBN: 97816055892991004
Publisher: ACM New York, NY, USA
Name and Venue of Conference: Conference on Human Factors in Computing Systems
Other identifier: 2001143

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