Monitoring dementia with automatic eye movements analysis

Yanxia Zhang, Thomas Wilcockson, Kwang In Kim, Trevor Jeremy Crawford, Hans-Werner Georg Gellersen, Peter Harvey Sawyer

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Eye movement patterns are found to reveal human cognitive and mental states that can not be easily measured by other biological signals. With the rapid development of eye tracking technologies, there are growing interests in analysing gaze data to infer information about people? cognitive states, tasks and activities performed in naturalistic environments. In this paper, we investigate the link between eye movements and cognitive function. We conducted experiments to record subject?s eye movements during video watching. By using computational methods, we identified eye movement features that are correlated to people?s cognitive health measures obtained through the standard cognitive tests. Our results show that it is possible to infer people?s cognitive function by analysing natural gaze behaviour. This work contributes an initial understanding of monitoring cognitive deterioration and dementia with automatic eye movement analysis.
Original languageEnglish
Title of host publicationIntelligent Decision Technologies 2016
PublisherSpringer
Pages299-309
Number of pages11
ISBN (Print)9783319396262
DOIs
Publication statusPublished - 9 Jun 2016

Publication series

NameSmart Innovation, Systems and Technologies

Keywords

  • Machine learning
  • Eye movements analysis
  • Health monitoring
  • Dementia
  • Cognitive function
  • COGNITIVE IMPAIRMENT
  • ALZHEIMERS-DISEASE
  • INHIBITORY CONTROL
  • MEMORY

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    Cite this

    Zhang, Y., Wilcockson, T., Kim, K. I., Crawford, T. J., Gellersen, H-W. G., & Sawyer, P. H. (2016). Monitoring dementia with automatic eye movements analysis. In Intelligent Decision Technologies 2016 (pp. 299-309). (Smart Innovation, Systems and Technologies). Springer. https://doi.org/10.1007/978-3-319-39627-9_26