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Computational and Mathematical Methods in Medicine
Volume 2018, Article ID 2676409, 13 pages
Review Article

Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer’s Disease: A Review

1Instituto Politécnico Nacional-CITEDI, Tijuana, BC, Mexico
2CONACYT, Ciudad de México, Mexico
3LaBRI, University of Bordeaux, Bordeaux, France
4Instituto Nacional de Geriatría, Ciudad de México, Mexico
5INSERM, University of Bordeaux, Bordeaux, France

Correspondence should be addressed to Jessica Beltrán; moc.liamg@nartlebacissej

Received 3 November 2017; Accepted 3 April 2018; Published 20 May 2018

Academic Editor: Hyuntae Park

Copyright © 2018 Jessica Beltrán et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


An opportune early diagnosis of Alzheimer’s disease (AD) would help to overcome symptoms and improve the quality of life for AD patients. Research studies have identified early manifestations of AD that occur years before the diagnosis. For instance, eye movements of people with AD in different tasks differ from eye movements of control subjects. In this review, we present a summary and evolution of research approaches that use eye tracking technology and computational analysis to measure and compare eye movements under different tasks and experiments. Furthermore, this review is targeted to the feasibility of pioneer work on developing computational tools and techniques to analyze eye movements under naturalistic scenarios. We describe the progress in technology that can enhance the analysis of eye movements everywhere while subjects perform their daily activities and give future research directions to develop tools to support early AD diagnosis through analysis of eye movements.