@inproceedings{2001143,
author={Eleanor Jones and  Jason Alexander and  Andreas Andreou and  Pourang Irani and Sriram Subramanian},
title={GesText: Accelerometer-based Gestural Text-Entry Systems},
booktitle={Conference on Human Factors in Computing Systems},
ISBN={978-1-60558-929-9/10/04},
publisher={ACM  New York, NY, USA},
month={April},
year={2010},
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.},
abstract-url={http://www.cs.bris.ac.uk/Publications/pub_master.jsp?id=2001143},
url={http://www.cs.bris.ac.uk/Publications/Papers/2001143.pdf},
keyword={},
pubtype={102}
}