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Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia

Dyslexia is a specific learning disorder that affects reading and writing abilities. Children with dyslexia are typically diagnosed during their primary school years, typically between the ages of 5 and 8, when their academic performance lags behind their peers. However, the diagnostic process can b...

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Main Authors: Siti Atiyah, Ali, Humaira, Nisar, Nurfaizatul Aisyah, Ab Aziz, Nor Asyikin, Fadzil, Nur Saida, Mohamad Zaber, Luthffi Idzhar, Ismail
Other Authors: Abdulhamit, Subasi
Format: Book Chapter
Language:English
Published: Academic Press 2024
Subjects:
T Technology (General)
Online Access:http://ir.unimas.my/id/eprint/46815/1/Springer%20Chapter%20in%20Book%202024-%20Dyslexia.pdf
http://ir.unimas.my/id/eprint/46815/
https://www.sciencedirect.com/science/article/abs/pii/B9780443291500000172
https://doi.org/10.1016/B978-0-443-29150-0.00017-2
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spelling my.unimas.ir-468152024-12-05T08:25:12Z http://ir.unimas.my/id/eprint/46815/ Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia Siti Atiyah, Ali Humaira, Nisar Nurfaizatul Aisyah, Ab Aziz Nor Asyikin, Fadzil Nur Saida, Mohamad Zaber Luthffi Idzhar, Ismail T Technology (General) Dyslexia is a specific learning disorder that affects reading and writing abilities. Children with dyslexia are typically diagnosed during their primary school years, typically between the ages of 5 and 8, when their academic performance lags behind their peers. However, the diagnostic process can be lengthy, and due to the diverse range of characteristics exhibited by individuals with dyslexia, misdiagnosis as other learning disabilities is not uncommon. This delay in diagnosis can result in delayed intervention, further exacerbating their learning challenges. This chapter aims to provide an understanding of the clinical procedures involved in diagnosing dyslexia alongside current interventions, followed by a discussion of electrophysiological processing differences between children with dyslexia and typically developing children. This involves identifying significant abnormalities in neurocognitive processing activity in brain signals provided by electroencephalography (EEG) during the resting state and event-related potential (ERP) during different task stimulations. Taking significant abnormalities existing between dyslexia and healthy children into account, the current technology of artificial intelligence and machine learning as tools for diagnosing and intervening in dyslexia using multimodel of brain signals is considered beneficial to enable the development of methods for early diagnosis and tailored interventions for children with dyslexia as young as possible. Academic Press Abdulhamit, Subasi Saeed Mian, Qaisar Humaira, Nisar 2024 Book Chapter PeerReviewed text en http://ir.unimas.my/id/eprint/46815/1/Springer%20Chapter%20in%20Book%202024-%20Dyslexia.pdf Siti Atiyah, Ali and Humaira, Nisar and Nurfaizatul Aisyah, Ab Aziz and Nor Asyikin, Fadzil and Nur Saida, Mohamad Zaber and Luthffi Idzhar, Ismail (2024) Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia. In: Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction : Artificial Intelligence Applications in Healthcare and Medicine. Academic Press, pp. 151-170. ISBN 978-0-443-29150-0 https://www.sciencedirect.com/science/article/abs/pii/B9780443291500000172 https://doi.org/10.1016/B978-0-443-29150-0.00017-2
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Siti Atiyah, Ali
Humaira, Nisar
Nurfaizatul Aisyah, Ab Aziz
Nor Asyikin, Fadzil
Nur Saida, Mohamad Zaber
Luthffi Idzhar, Ismail
Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
description Dyslexia is a specific learning disorder that affects reading and writing abilities. Children with dyslexia are typically diagnosed during their primary school years, typically between the ages of 5 and 8, when their academic performance lags behind their peers. However, the diagnostic process can be lengthy, and due to the diverse range of characteristics exhibited by individuals with dyslexia, misdiagnosis as other learning disabilities is not uncommon. This delay in diagnosis can result in delayed intervention, further exacerbating their learning challenges. This chapter aims to provide an understanding of the clinical procedures involved in diagnosing dyslexia alongside current interventions, followed by a discussion of electrophysiological processing differences between children with dyslexia and typically developing children. This involves identifying significant abnormalities in neurocognitive processing activity in brain signals provided by electroencephalography (EEG) during the resting state and event-related potential (ERP) during different task stimulations. Taking significant abnormalities existing between dyslexia and healthy children into account, the current technology of artificial intelligence and machine learning as tools for diagnosing and intervening in dyslexia using multimodel of brain signals is considered beneficial to enable the development of methods for early diagnosis and tailored interventions for children with dyslexia as young as possible.
author2 Abdulhamit, Subasi
author_facet Abdulhamit, Subasi
Siti Atiyah, Ali
Humaira, Nisar
Nurfaizatul Aisyah, Ab Aziz
Nor Asyikin, Fadzil
Nur Saida, Mohamad Zaber
Luthffi Idzhar, Ismail
format Book Chapter
author Siti Atiyah, Ali
Humaira, Nisar
Nurfaizatul Aisyah, Ab Aziz
Nor Asyikin, Fadzil
Nur Saida, Mohamad Zaber
Luthffi Idzhar, Ismail
author_sort Siti Atiyah, Ali
title Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
title_short Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
title_full Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
title_fullStr Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
title_full_unstemmed Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
title_sort understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia
publisher Academic Press
publishDate 2024
url http://ir.unimas.my/id/eprint/46815/1/Springer%20Chapter%20in%20Book%202024-%20Dyslexia.pdf
http://ir.unimas.my/id/eprint/46815/
https://www.sciencedirect.com/science/article/abs/pii/B9780443291500000172
https://doi.org/10.1016/B978-0-443-29150-0.00017-2
_version_ 1817848783504932864
score 13.223943

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