Assessing Levels of Attention Using Low Cost Eye Tracking

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Abstract

The emergence of mobile eye trackers embedded in next generation smartphones or VR displays will make it possible to trace not only what objects we look at but also the level of attention in a given situation. Exploring whether we can quantify the engagement of a user interacting with a laptop, we apply mobile eye tracking in an in-depth study over 2 weeks with nearly 10.000 observations to assess pupil size changes, related to attentional aspects of alertness, orientation and conflict resolution. Visually presenting conflicting cues and targets we hypothesize that it’s feasible to measure the allocated effort when responding to confusing stimuli. Although such experiments are normally carried out in a lab, we have initial indications that we are able to differentiate between sustained alertness and complex decision making even with low cost eye tracking “in the wild”. From a quantified self perspective of individual behavioural adaptation, the correlations between the pupil size and the task dependent reaction time and error rates may longer term provide a foundation for modifying smartphone content and interaction to the users perceived level of attention.
Original languageEnglish
Title of host publicationProceedings of the 10th International Conference on Universal Access in Human-Computer Interaction (UAHCI 2016) : Part I
PublisherSpringer
Publication date2016
Pages409-420
ISBN (Print)978-3-319-40249-9
ISBN (Electronic)978-3-319-40250-5
DOIs
Publication statusPublished - 2016
Event10th International Conference on Universal Access in Human-Computer Interaction - Toronto, Canada
Duration: 17 Jul 201622 Jul 2016
Conference number: 10
http://2016.hci.international/uahci

Conference

Conference10th International Conference on Universal Access in Human-Computer Interaction
Number10
Country/TerritoryCanada
CityToronto
Period17/07/201622/07/2016
Internet address
SeriesLecture Notes in Computer Science
Volume9737
ISSN0302-9743

Keywords

  • Eye tracking
  • Attention network

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