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Title: Selection strategies in gaze interaction
Authors: Mollenbach, Emilie
Issue Date: 2010
Publisher: © Emilie Mollenbach
Abstract: This thesis deals with selection strategies in gaze interaction, specifically for a context where gaze is the sole input modality for users with severe motor impairments. The goal has been to contribute to the subfield of assistive technology where gaze interaction is necessary for the user to achieve autonomous communication and environmental control. From a theoretical point of view research has been done on the physiology of the gaze, eye tracking technology, and a taxonomy of existing selection strategies has been developed. Empirically two overall approaches have been taken. Firstly, end-user research has been conducted through interviews and observation. The capabilities, requirements, and wants of the end-user have been explored. Secondly, several applications have been developed to explore the selection strategy of single stroke gaze gestures (SSGG) and aspects of complex gaze gestures. The main finding is that single stroke gaze gestures can successfully be used as a selection strategy. Some of the features of SSGG are: That horizontal single stroke gaze gestures are faster than vertical single stroke gaze gestures; That there is a significant difference in completion time depending on gesture length; That single stroke gaze gestures can be completed without visual feedback; That gaze tracking equipment has a significant effect on the completion times and error rates of single stroke gaze gestures; That there is not a significantly greater chance of making selection errors with single stroke gaze gestures compared with dwell selection. The overall conclusion is that the future of gaze interaction should focus on developing multi-modal interactions for mono-modal input.
Description: A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.
URI: https://dspace.lboro.ac.uk/2134/8101
Appears in Collections:PhD Theses (Computer Science)

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