@inproceedings{efa735f48eb54b0bb6fd8bc9fde6aa52,
title = "GesText: Accelerometer-Based Gestural Text-Entry Systems",
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.",
author = "Eleanor Jones and Jason Alexander and Andreas Andreou and Pourang Irani and Sriram Subramanian",
year = "2010",
month = apr,
day = "10",
doi = "10.1145/1753326.1753655",
language = "English",
isbn = "978-1-60558-929-9",
series = "CHI '10",
publisher = "Association for Computing Machinery",
pages = "2173--2182",
booktitle = "Proceedings of the 28th International Conference on Human Factors in Computing Systems (CHI'10)",
address = "USA United States",
}