A systematic review of research dimensions towards dyslexia screening using machine learning
TG Jan, SM Khan - Journal of The Institution of Engineers (India): Series B, 2023 - Springer
Dyslexia is the hidden learning disability, neurobiological in origin wherein students face
hard time in accurate or fluent word recognition, connecting letters to the sounds. In India …
hard time in accurate or fluent word recognition, connecting letters to the sounds. In India …
DICE-net: a novel convolution-transformer architecture for Alzheimer detection in EEG signals
Objective: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects
a significant percentage of the elderly. EEG has emerged as a promising tool for the timely …
a significant percentage of the elderly. EEG has emerged as a promising tool for the timely …
EEG based classification of children with learning disabilities using shallow and deep neural network
NPG Seshadri, S Agrawal, BK Singh… - … Signal Processing and …, 2023 - Elsevier
Learning disability (LD), a neurodevelopmental disorder that has severely impacted the lives
of many children all over the world. LD refers to significant deficiency in children's reading …
of many children all over the world. LD refers to significant deficiency in children's reading …
[HTML][HTML] A Review of Artificial Intelligence-Based Dyslexia Detection Techniques
Y Alkhurayyif, ARW Sait - Diagnostics, 2024 - mdpi.com
Problem: Dyslexia is a learning disorder affecting an individual's ability to recognize words
and understand concepts. It remains underdiagnosed due to its complexity and …
and understand concepts. It remains underdiagnosed due to its complexity and …
A dataset of scalp EEG recordings of Alzheimer's disease, frontotemporal dementia and healthy subjects from routine EEG
Recently, there has been a growing research interest in utilizing the electroencephalogram
(EEG) as a non-invasive diagnostic tool for neurodegenerative diseases. This article …
(EEG) as a non-invasive diagnostic tool for neurodegenerative diseases. This article …
Assessing electroencephalography as a stress indicator: a VR high-altitude scenario monitored through EEG and ECG
Over the last decade, virtual reality (VR) has become an increasingly accessible commodity.
Head-mounted display (HMD) immersive technologies allow researchers to simulate …
Head-mounted display (HMD) immersive technologies allow researchers to simulate …
Evaluating the window size's role in automatic EEG epilepsy detection
Electroencephalography is one of the most commonly used methods for extracting
information about the brain's condition and can be used for diagnosing epilepsy. The EEG …
information about the brain's condition and can be used for diagnosing epilepsy. The EEG …
An ensemble-based machine learning technique for dyslexia detection during a visual continuous performance task
Background Dyslexia is a neurological disorder which affects the learning of individuals
suffering from it, especially children. It causes reading and writing difficulties, leading to …
suffering from it, especially children. It causes reading and writing difficulties, leading to …
Inter-subject prediction of pediatric emergence delirium using feature selection and classification from spontaneous EEG signals
Pediatric emergence delirium is a troublesome clinical phenomenon, which may cause
serious safety problems and sequelae. Predicting pediatric emergence delirium before …
serious safety problems and sequelae. Predicting pediatric emergence delirium before …
Enhanced Alzheimer's disease and Frontotemporal Dementia EEG Detection: Combining lightGBM Gradient Boosting with Complexity Features
Alzheimer's disease and Frontotemporal dementia are the two most reported dementia
cases. They both are neurodegenerative disorders without cure while existing treatments …
cases. They both are neurodegenerative disorders without cure while existing treatments …