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Hans Gellersen

Monitoring dementia with automatic eye movements analysis

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

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
EditorsIreneusz Czarnowski, Alfonso Mateos Caballero, Robert J. Howlett, Lakhmi C. Jain
Number of pages11
Publisherspringer
Publication year18 Jun 2016
Pages299-309
ISBN (print)9783319396262
DOIs
Publication statusPublished - 18 Jun 2016
Externally publishedYes
SeriesSmart Innovation, Systems and Technologies

    Research areas

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

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