2022
DOI: 10.3389/fcomp.2021.628634
|View full text |Cite
|
Sign up to set email alerts
|

A Universal Screening Tool for Dyslexia by a Web-Game and Machine Learning

Abstract: Children with dyslexia have difficulties learning how to read and write. They are often diagnosed after they fail school even if dyslexia is not related to general intelligence. Early screening of dyslexia can prevent the negative side effects of late detection and enables early intervention. In this context, we present an approach for universal screening of dyslexia using machine learning models with data gathered from a web-based language-independent game. We designed the game content taking into considerati… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4
2

Relationship

0
6

Authors

Journals

citations
Cited by 7 publications
(1 citation statement)
references
References 47 publications
0
1
0
Order By: Relevance
“…However, implementation of the scientific results in terms of eye tracking during reading, in practice, is not abundantly present. There are tools reported in the scientific literature that focus on the digitalization of dyslexia diagnosis [ 46 , 47 ], some of which do use eye tracking [ 38 ], but considering the variety of study conditions including eye trackers used, text presentation, native language, participant age, and many others, this makes practical applications somewhat complicated and difficult. Providing feedback during reading in terms of exact points in the text that caused struggles would also be quite difficult, considering that few eye-tracking processing techniques can pinpoint the locations in the text that were problematic to read.…”
Section: Introductionmentioning
confidence: 99%
“…However, implementation of the scientific results in terms of eye tracking during reading, in practice, is not abundantly present. There are tools reported in the scientific literature that focus on the digitalization of dyslexia diagnosis [ 46 , 47 ], some of which do use eye tracking [ 38 ], but considering the variety of study conditions including eye trackers used, text presentation, native language, participant age, and many others, this makes practical applications somewhat complicated and difficult. Providing feedback during reading in terms of exact points in the text that caused struggles would also be quite difficult, considering that few eye-tracking processing techniques can pinpoint the locations in the text that were problematic to read.…”
Section: Introductionmentioning
confidence: 99%