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Computational Methods to Infer Human Factors for Adaptation and Personalization Using Eye Tracking

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A Human-Centered Perspective of Intelligent Personalized Environments and Systems

Part of the book series: Human–Computer Interaction Series ((HCIS))

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Abstract

“The Eyes Are the Window to the Soul” is a commonly used phrase that refers to the intricate relationship between a person's eyes and their underlying thought processes and affective states. Indeed, researchers in perceptual and cognitive psychology have long studied a user's eye movements in order to understand attention patterns and emotional responses to stimuli. More recently, researchers in Human–Computer Interaction and Artificial Intelligence have started to study the potential of using eye tracking to infer a user's underlying human factors, in order to drive personalized systems that adapt to an individual user's abilities, traits, and states. This chapter provides an overview of eye tracking technology, as well as a review of the various eye movement features that may be calculated from eye tracking data. This is followed by a review of various modeling techniques that use these features to infer human factors, as well as a range of application scenarios and examples. Lastly, the chapter concludes with an outlook on the use of eye tracking technology for human factor inference, including both challenges and opportunities.

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Author information

Authors and Affiliations

  1. California State Polytechnic University, Pomona, CA, 91768, USA

    Ben Steichen

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  1. Ben Steichen
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Correspondence to Ben Steichen .

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Editors and Affiliations

  1. Department of Computer Science and Informatics, Jönköping University, School of Engineering, Jönköping, Sweden

    Bruce Ferwerda

  2. Human-Centric SARL, Paris, France

    Mark Graus

  3. UX Industries & Customer Experience, Product Engineering, SAP SE, Intelligent Enterprise Group, Walldorf, Baden-Württemberg, Germany

    Panagiotis Germanakos

  4. University of Primorska, Koper, Slovenia

    Marko Tkalčič

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Steichen, B. (2024). Computational Methods to Infer Human Factors for Adaptation and Personalization Using Eye Tracking. In: Ferwerda, B., Graus, M., Germanakos, P., Tkalčič, M. (eds) A Human-Centered Perspective of Intelligent Personalized Environments and Systems. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-031-55109-3_7

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  • DOI: https://doi.org/10.1007/978-3-031-55109-3_7

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