BELTRAN, J.; GARCIA-VAZQUEZ, M. S.; BENOIS-PINEAU, J.; GUTIERREZ-ROBLEDO, L. M.; DARTIGUES, Jean-Francois

doi:10.1155/2018/2676409

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Computational and Mathematical Methods in Medicine. 2018, vol. 2018, p. 2676409

Résumé en anglais

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.< Réduire

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https://oskar-bordeaux.fr/handle/20.500.12278/11443

DOI

http://dx.doi.org/10.1155/2018/2676409

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Bordeaux Population Health Research Center (BPH) - UMR 1219

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

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