Developmental dyslexia detection using machine learning techniques : A survey

Abstract

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.

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