Screening Dyslexia Using Visual Auditory Computer Games and Machine Learning

被引:0
|
作者
Rauschenberger, Maria [1 ]
Baeza-Yates, Ricardo [2 ]
Rello, Luz [3 ]
机构
[1] Univ Appl Sci Emden Leer, Fac Technol, D-26723 Emden, Germany
[2] Northeastern Univ Silicon Valley, Inst Experiential AI, San Jose, CA 95113 USA
[3] IE Univ, IE Business Sch, Madrid 28046, Spain
来源
IEEE ACCESS | 2025年 / 13卷
关键词
Dyslexia; language disorder; language-independence; Machine learning; reading disorder; dyslexia screening; serious games; machine learning; ATTENTION; CHILDREN;
D O I
10.1109/ACCESS.2025.3539719
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reading acquisition is one the main keys for school success and a crucial component for empowering individuals to participate meaningfully in society. Yet, it is still a challenging skill to acquire for around 10% of children that have dyslexia, a type of neuro-developmental disorder that affects the ability to learn how to read and write. Dyslexia is often under-diagnosed, and normally children with dyslexia are only detected once they fail in school, even though dyslexia is not related to general intelligence. In this work, we present an approach for screening dyslexia using language-independent games in combination with machine learning models. To reach this goal, we designed the content of a computer game, collected data from 137 children playing this game (51 with dyslexia) in different languages -German, Spanish and English- and created a prediction model using different machine learning classifiers. Our method provides a precision of 0.78 and recall of 0.79 for German and a precision of 0.83 and recall of 0.80 for all languages when Extra Trees are used, with an accuracy of 0.67 and 0.75, respectively. Our results open the possibility of inexpensive online early screening of dyslexia for young children using non-linguistic elements.
引用
收藏
页码:29541 / 29553
页数:13
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