The use of eye movements in human-computer interaction techniques: what you look at is what you get
ACM Transactions on Information Systems (TOIS) - Special issue on computer—human interaction
Twenty years of eye typing: systems and design issues
ETRA '02 Proceedings of the 2002 symposium on Eye tracking research & applications
Phrase sets for evaluating text entry techniques
CHI '03 Extended Abstracts on Human Factors in Computing Systems
Text Entry Systems: Mobility, Accessibility, Universality
Text Entry Systems: Mobility, Accessibility, Universality
Eye typing using word and letter prediction and a fixation algorithm
Proceedings of the 2008 symposium on Eye tracking research & applications
Writing with Your Eye: A Dwell Time Free Writing System Adapted to the Nature of Human Eye Gaze
PIT '08 Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems
Fast gaze typing with an adjustable dwell time
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Dwell-based pointing in applications of human computer interaction
INTERACT'07 Proceedings of the 11th IFIP TC 13 international conference on Human-computer interaction
Object selection in gaze controlled systems: What you don't look at is what you get
ACM Transactions on Applied Perception (TAP)
An exploratory study of eye typing fundamentals: dwell time, text entry rate, errors, and workload
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Comparison of video-based pointing and selection techniques for hands-free text entry
Proceedings of the International Working Conference on Advanced Visual Interfaces
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In eye typing systems, a dwell time that adjusts to the user's natural typing speed is highly desirable. We present an algorithm for on-line adjustment of dwell time developed after detailed analysis of exit time upon selection of virtual keys. Exit time was measured using a wide range of dwell times for key selection (300-1100 ms). The results suggest that there was considerable variability in exit time among users indicating the need for calibration of the algorithm. The algorithm was evaluated in a user study and proved to be efficient. We also discuss the shortcomings of the current algorithm's implementation.