Attentive interfaces for users with disabilities: eye gaze for intention and uncertainty estimation

De Montfort University Open Research Archive

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dc.contributor.author Prendinger, Helmut en
dc.contributor.author Hyrskykari, Aulikki en
dc.contributor.author Nakayama, Minoru en
dc.contributor.author Istance, Howell en
dc.contributor.author Bee, Nikolaus en
dc.contributor.author Takahasi, Yosiyuki en
dc.date.accessioned 2012-04-11T13:46:22Z
dc.date.available 2012-04-11T13:46:22Z
dc.date.issued 2009
dc.identifier.citation Prendinger, H., Hyrskykari, A., Nakayama, M., Istance, H., Bee, N. and Takahasi, Y. (2009) Attentive interfaces for users with disabilities: eye gaze for intention and uncertainty estimation. Universal Access in the Information Society, 8, (4), pp 339-354 en
dc.identifier.issn 16155289
dc.identifier.uri http://hdl.handle.net/2086/5898
dc.description.abstract Attentive user interfaces (AUIs) capitalize on the rich information that can be obtained from users' gaze behavior in order to infer relevant aspects of their cognitive state. Not only is eye gaze an excellent clue to states of interest and intention, but also to preference and confidence in comprehension. AUIs are built with the aim of adapting the interface to the user's current information need, and thus reduce workload of interaction. Given those characteristics, it is believed that AUIs can have particular benefits for users with severe disabilities, for whom operating a physical device (like a mouse pointer) might be very strenuous or infeasible. This paper presents three studies that attempt to gauge uncertainty and intention on the part of the user from gaze data, and compare the success of each approach. The paper discusses how the application of the approaches adopted in each study to user interfaces can support users with severe disabilities. en
dc.language.iso en en
dc.subject attentive interfaces en
dc.subject disabilities en
dc.subject eye gaze en
dc.title Attentive interfaces for users with disabilities: eye gaze for intention and uncertainty estimation en
dc.type Article en
dc.identifier.doi http://dx.doi.org/10.1007/s10209-009-0144-5
dc.researchgroup Centre for Computational Intelligence en


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