Review of EEG-based pattern classification frameworks for dyslexia

Harshani Perera,Kok Wai Wong,Mohd Fairuz Shiratuddin

doi:10.1186/s40708-018-0079-9

Abstract

Dyslexia is a disability that causes difficulties in reading and writing despite average intelligence. This hidden disability often goes undetected since dyslexics are normal and healthy in every other way. Electroencephalography (EEG) is one of the upcoming methods being researched for identifying unique brain activation patterns in dyslexics. The aims of this paper are to examine pros and cons of existing EEG-based pattern classification frameworks for dyslexia and recommend optimisations through the findings to assist future research. A critical analysis of the literature is conducted focusing on each framework’s (1) data collection, (2) pre-processing, (3) analysis and (4) classification methods. A wide range of inputs as well as classification approaches has been experimented for the improvement in EEG-based pattern classification frameworks. It was uncovered that incorporating reading- and writing-related tasks to experiments used in data collection may help improve these frameworks instead of using only simple tasks, and those unwanted artefacts caused by body movements in the EEG signals during reading and writing activities could be minimised using artefact subspace reconstruction. Further, support vector machine is identified as a promising classifier to be used in EEG-based pattern classification frameworks for dyslexia.

Highlights

Dyslexia is a disability that involves deficiencies in reading and writing capabilities, but does not affect intellect
1.1 What is dyslexia? Dyslexia is a disability with a neurological origin that causes difficulties in reading, writing or spelling despite average or above average intelligence and sensory abilities
5 Conclusion Dyslexia is a disability with a neurological origin, affecting a significant amount of the population, which causes difficulties in reading and writing despite average intelligence

Summary

Introduction

Dyslexia is a disability that involves deficiencies in reading and writing capabilities, but does not affect intellect. Each framework is assessed using a pre-defined format to arrange the data in a meaningful manner and to recognise its strengths and weaknesses These discoveries are used to propose an improved EEG-based pattern classification framework for dyslexia (higher validation accuracies for the classifier). Promising results have shown of children who go through such intervention programs in the early stages [24] proving improvement in reading performance as well as reduction in anxiety [25] Though these techniques help, dyslexia still does persist into adulthood [26]. 1.3 Conventional dyslexia detection techniques The conventional dyslexia detection practices are often based on ‘behavioural’ symptoms and aspects [28] Standardised test such as Wechsler Individual Achievement Test (WIAT), Comprehensive Test of Phonological Processing (CTOPP), Oral and Written Language Scales (OWLS) and Woodcock Johnson (WJ) are used to assess reading, writing, intelligence quotient and phonological processing abilities. Number of particpants (test and control group), gender diversity within the groups, age range, participant inclusion and exclusion criteria, Experiment, EEG channels used

Conclusion

What are the existing frameworks and their shortcomings?

Findings