Dyslexia Diagnostics Based on Eye Movements and Artificial Intelligence Methods: A Review

Author:

Gracheva M.A.1ORCID,Shalileh S.2ORCID

Affiliation:

1. Institute for Information Transmission Problems (Kharkevich Institute)

2. HSE University

Abstract

<p style="text-align: justify;">The review considers methods of dyslexia diagnostics based on eye movement data and implemented on the basis of artificial intelligence. A number of studies have shown that eye movements in people with dyslexia may differ from those of people with normal reading abilities. Since 2015, studies have begun to appear in which the eye movements of observers with and without dyslexia were analyzed using various artificial intelligence methods. To date, there are a number of papers using both simple and more complex models (with neural networks and deep learning). This review discusses what accuracy of diagnosis has been achieved by researchers, for which groups of subjects and for which languages the current results have been shown, what types of algorithms have been used, and other practical aspects of conducting such diagnosis. According to the data analyzed, dyslexia diagnostics by eye movements and artificial intelligence methods is very promising and may have a significant impact on early diagnosing of reading problems.</p>

Publisher

Moscow State University of Psychology and Education

Subject

General Medicine

Reference71 articles.

1. Akhutina T.V., Inshakova O.B. Neiropsikhologicheskaya diagnostika, obsledovanie pis'ma i chteniya mladshikh shkol'nikov [Neuropsychological diagnostics, examination of writing and reading of younger students]. Moscow: V. Sekachev, 2016. 180 p. (In Russ.).

2. Barabanshchikov V.A., Zhegallo A.V. Aitreking: Metody registratsii dvizhenii glaz v psikhologicheskikh issledovaniyakh i praktike [Eyetracking: Methods of eye movements registration in psychological research and practice]. Moscow: Kogito-Tsentr, 2014. 128 p. (In Russ.).

3. Bezrukikh M.M. Trudnosti obucheniya v nachal'noi shkole. Prichiny, diagnostika, kompleksnaya pomoshch' [Learning difficulties in elementary school. Causes, diagnosis, complex help]. Moscow: Eksmo, 2009. 464 p. (In Russ.).

4. Glozman Zh.M., Potanina A.YU., Soboleva A.E. Neiropsikhologicheskaya diagnostika v doshkol'nom vozraste [Neuropsychological diagnostics in preschool age], 2nd ed. Saint-Petersburg: Piter, 2008. 80 p. (In Russ.).

5. Gol'dina S.M., Laurinavichyute A.K., Lopukhina A.A. et al. Osobennosti dvizhenii glaz pri chtenii u detei s disleksiei. Proceedings of the First National congress on cognitive research, artificial intelligence and neuroinformatics, Moscow, October 10–16, 2020. Vol. 1. Moscow: Natsional'nyi issledovatel'skii yadernyi universitet "MIFI", 2021, pp. 497–500. (In Russ.).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3