Developmental dyslexia detection using machine learning techniques : A survey

被引:22
作者
Kaisar, Shahriar [1 ]
机构
[1] RMIT Univ, Sch Business IT & Logist, Melbourne, Vic, Australia
来源
ICT EXPRESS | 2020年 / 6卷 / 03期
关键词
Dyslexia; Machine learning; Survey; EEG;
D O I
10.1016/j.icte.2020.05.006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Developmental dyslexia is a learning disability that occurs mostly in children during their early childhood. Dyslexic children face difficulties while reading, spelling and writing words despite having average or above-average intelligence. As a consequence, dyslexic children often suffer from negative feelings, such as low self-esteem, frustration, and anger. Therefore, early detection of dyslexia is very important to support dyslexic children right from the start. Researchers have proposed a wide range of techniques to detect developmental dyslexia, which includes game-based techniques, reading and writing tests, facial image capture and analysis, eye tracking, Magnetic reasoning imaging (MRI) and Electroencephalography (EEG) scans. This survey paper critically analyzes recent contributions in detecting dyslexia using machine learning techniques and identify potential opportunities for future research. (C) 2020 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V.
引用
收藏
页码:181 / 184
页数:4
相关论文
共 20 条
  • [1] [Anonymous], 2020, Dyslexia
  • [2] [Anonymous], 2020, WHAT IS DYSLEXIA
  • [3] [Anonymous], 2020, DYSLEXIA IN AUSTRALI
  • [4] Asvestopoulou T., 2019, DYSLEXML SCREENING T
  • [5] Ballesteros M., 2015, W4A 15 P 12 WEB ALL, P1, DOI 10.1145/2745555.2746644 Salvucci
  • [6] Screening for Dyslexia Using Eye Tracking during Reading
    Benfatto, Mattias Nilsson
    Seimyr, Gustaf Oqvist
    Ygge, Jan
    Pansell, Tony
    Rydberg, Agneta
    Jacobson, Christer
    [J]. PLOS ONE, 2016, 11 (12):
  • [7] Disrupted white matter connectivity underlying developmental dyslexia: A machine learning approach
    Cui, Zaixu
    Xia, Zhichao
    Su, Mengmeng
    Shu, Hua
    Gong, Gaolang
    [J]. HUMAN BRAIN MAPPING, 2016, 37 (04) : 1443 - 1458
  • [8] Frid A., 2018, ARXIV PREPRINT ARXIV
  • [9] Dyslexia Adaptive Learning Model: Student Engagement Prediction Using Machine Learning Approach
    Hamid, Siti Suhaila Abdul
    Admodisastro, Novia
    Manshor, Noridayu
    Kamaruddin, Azrina
    Abd Ghani, Abdul Azim
    [J]. RECENT ADVANCES ON SOFT COMPUTING AND DATA MINING (SCDM 2018), 2018, 700 : 372 - 384
  • [10] Hamid SSA, 2015, 2015 9TH MALAYSIAN SOFTWARE ENGINEERING CONFERENCE (MYSEC2015), P284, DOI 10.1109/MySEC.2015.7475234