Monitoring Dementia with Automatic Eye Movements Analysis
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.
KeywordsMachine learning Eye movements analysis Health monitoring Dementia Cognitive function
The work described in this paper is funded by EPSRC project EP/M006255/1 Monitoring Of Dementia using Eye Movements (MODEM).
- 2.Bednarik, R., Vrzakova, H., Hradis, M.: What do you want to do next: a novel approach for intent prediction in gaze-based interaction. In: Procedings of ETRA 2012, ETRA ’12, pp. 83–90. ACM, New York, NY, USA (2012)Google Scholar
- 3.Benson, P.J., Beedie, S.A., Shephard, E., Giegling, I., Rujescu, D., Clair, D.S.: Simple viewing tests can detect eye movement abnormalities that distinguish schizophrenia cases from controls with exceptional accuracy. Biol. Psychiatry 72(9), 716–724 (2012). Cortical Inhibition Deficits in SchizophreniaCrossRefGoogle Scholar
- 6.Crabb, D.P., Smith, N.D., Zhu, H.: What’s on tv? detecting age-related neurodegenerative eye disease using eye movement scanpaths. Frontiers Aging Neurosci. 6(312) (2014)Google Scholar
- 14.Jang, Y.M., Lee, S., Mallipeddi, R., Kwak, H.W., Lee, M.: Recognition of human’s implicit intention based on an eyeball movement pattern analysis. In: Lu, B.L., Zhang, L., Kwok, J. (eds.) Neural Information Processing. Lecture Notes in Computer Science, vol. 7062, pp. 138–145. Springer, Heidelberg (2011)CrossRefGoogle Scholar
- 15.Jimison, H., Jessey, N., McKanna, J., Zitzelberger, T., Kaye, J.: Monitoring computer interactions to detect early cognitive impairment in elders. In: 1st Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare, 2006. D2H2, pp. 75–78. IEEE (2006)Google Scholar
- 16.Kardan, O., Berman, M.G., Yourganov, G., Schmidt, J., Henderson, J.M.: Classifying mental states from eye movements during scene viewing (2015)Google Scholar
- 17.Knapp, M., Prince, M., Albanese, E., Banerjee, S., Dhanasiri, S., Fernandez, J., Ferri, C., Snell, T., Stewart, R.: Dementia uk: report to the alzheimer’s society. Kings College London and London School of Economics and Political Science (2007)Google Scholar
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 2.5 International License (http://creativecommons.org/licenses/by-nc/2.5/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.