A comprehensive review of machine learning approaches for dyslexia diagnosis

N Ahire, RN Awale, S Patnaik, A Wagh - Multimedia Tools and …, 2023 - Springer
Electroencephalography (EEG) is the commonly employed electro-biological imaging
technique for diagnosing brain functioning. The EEG signals are used to determine head …

Classification of EEG signals from young adults with dyslexia combining a Brain Computer Interface device and an Interactive Linguistic Software Tool

P Christodoulides, A Miltiadous, KD Tzimourta… - … Signal Processing and …, 2022 - Elsevier
The magnocellular pathway deficit theory has long been considered to be a possible cause
for dyslexia, providing an alternative method to explain auditory and visual processing …

Investigating issues and needs of dyslexic students at university: Proof of concept of an artificial intelligence and virtual reality-based supporting platform and …

A Zingoni, J Taborri, V Panetti, S Bonechi… - Applied Sciences, 2021 - mdpi.com
Featured Application The outcomes of this work can represent a turning point toward a more
and more inclusive university environment for dyslexic students, at the same time showing …

EEG based functional brain network analysis and classification of dyslexic children during sustained attention task

NPG Seshadri, BK Singh… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reading is a complex cognitive skill that involves visual, attention, and linguistic skills.
Because attention is one of the most important cognitive skills for reading and learning, the …

A novel approach for detection of dyslexia using convolutional neural network with EOG signals

R Ileri, F Latifoğlu, E Demirci - Medical & Biological Engineering & …, 2022 - Springer
Dyslexia is a learning disability in acquiring reading skills, even though the individual has
the appropriate learning opportunity, adequate education, and appropriate sociocultural …

A review of electroencephalogram-based analysis and classification frameworks for dyslexia

H Perera, MF Shiratuddin, KW Wong - … 2016, Kyoto, Japan, October 16–21 …, 2016 - Springer
Dyslexia is a hidden learning disability that causes difficulties in reading and writing despite
average intelligence. Electroencephalogram (EEG) is one of the upcoming methods being …

Review of EEG-based pattern classification frameworks for dyslexia

H Perera, MF Shiratuddin, KW Wong - Brain informatics, 2018 - Springer
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 …

Changes in EEG complexity with neurofeedback and multi-sensory learning in children with dyslexia: A multiscale entropy analysis

G Eroğlu, M Gürkan, S Teber, K Ertürk… - Applied …, 2022 - Taylor & Francis
Multiscale entropy analysis (MSE) is a novel entropy-based approach for measuring
dynamical complexity in physiological systems over a range of temporal scales. MSE has …

[PDF][PDF] Multiscaled complexity analysis of EEG epileptic seizure using entropy-based techniques

L Hussain, S Saeed, IA Awan, A Idris - Archives of Neuroscience, 2018 - brieflands.com
Objectives: The most common chronic disorder due to sudden change in the electrical
activity of the brain is known as epilepsy. It causes millions of deaths every year and is the …

Optimized KNN classify rule for EEG based differentiation between capable dyslexic and normal children

AZA Zainuddin, KY Lee, W Mansor… - 2016 IEEE EMBS …, 2016 - ieeexplore.ieee.org
Information on brain state and functionality could be obtained from Electroencephalograph
(EEG) signal and is suitable to be used in analyzing brain disorders such as dyslexia. Our …