Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA)
Learning disability (LD) is a neurological processing disorder that causes impediment in processing and understanding information. LD is not only affecting academic performance but can also influence on relationship with family, friends and colleagues. Hence, it is important to detect the learni...
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| Format: | Article |
| Language: | English English |
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Institute of Advanced Engineering and Science
2020
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| Online Access: | http://irep.iium.edu.my/80698/ http://irep.iium.edu.my/80698/13/Detecting%20learning%20disabilities%20based%20on%20neuro-physiological%20interface%20of%20affect_fulltext.pdf http://irep.iium.edu.my/80698/14/80698_Detecting%20learning%20disabilities%20based%20on%20neuro-physiological%20interface%20of%20affect_SCOPUS.pdf |
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| author | Mat Razi, Nurul Izzati Abdul Rahman, Abdul Wahab Kamaruddin, Norhaslinda |
| author_facet | Mat Razi, Nurul Izzati Abdul Rahman, Abdul Wahab Kamaruddin, Norhaslinda |
| author_sort | Mat Razi, Nurul Izzati |
| building | IIUM Repository |
| collection | Online Access |
| description | Learning disability (LD) is a neurological processing disorder that causes
impediment in processing and understanding information. LD is not only
affecting academic performance but can also influence on relationship
with family, friends and colleagues. Hence, it is important to detect the
learning disabilities among children prior to the school year to avoid from
anxiety, bully and other social problems. This research aims to implement the
learning disabilities detection based on the emotions captured from
electroencephalogram (EEG) to recognize the symptoms of Autism Spectrum
Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and
dyslexia in order to have early diagnosis and assisting the clinician evaluation.
The results show several symptoms that ASD children have low alpha power
with the Alpha-Beta Test (ABT) power ratio and ASD U-shaped graph, ADHD
children have high Theta-Beta Test (TBT) power ratio while Dyslexia have
high Left-over-Right Theta (LRT) power ratio. This can be concluded that
the learning disabilities detection methods proposed in this study is applicable
for ASD, ADHD and also Dyslexia diagnosis. |
| first_indexed | 2025-11-14T17:49:51Z |
| format | Article |
| id | iium-80698 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T17:49:51Z |
| publishDate | 2020 |
| publisher | Institute of Advanced Engineering and Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-806982020-11-10T08:10:34Z http://irep.iium.edu.my/80698/ Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) Mat Razi, Nurul Izzati Abdul Rahman, Abdul Wahab Kamaruddin, Norhaslinda Q Science (General) Learning disability (LD) is a neurological processing disorder that causes impediment in processing and understanding information. LD is not only affecting academic performance but can also influence on relationship with family, friends and colleagues. Hence, it is important to detect the learning disabilities among children prior to the school year to avoid from anxiety, bully and other social problems. This research aims to implement the learning disabilities detection based on the emotions captured from electroencephalogram (EEG) to recognize the symptoms of Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD) and dyslexia in order to have early diagnosis and assisting the clinician evaluation. The results show several symptoms that ASD children have low alpha power with the Alpha-Beta Test (ABT) power ratio and ASD U-shaped graph, ADHD children have high Theta-Beta Test (TBT) power ratio while Dyslexia have high Left-over-Right Theta (LRT) power ratio. This can be concluded that the learning disabilities detection methods proposed in this study is applicable for ASD, ADHD and also Dyslexia diagnosis. Institute of Advanced Engineering and Science 2020-07 Article PeerReviewed application/pdf en http://irep.iium.edu.my/80698/13/Detecting%20learning%20disabilities%20based%20on%20neuro-physiological%20interface%20of%20affect_fulltext.pdf application/pdf en http://irep.iium.edu.my/80698/14/80698_Detecting%20learning%20disabilities%20based%20on%20neuro-physiological%20interface%20of%20affect_SCOPUS.pdf Mat Razi, Nurul Izzati and Abdul Rahman, Abdul Wahab and Kamaruddin, Norhaslinda (2020) Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA). Indonesian Journal of Electrical Engineering and Computer Science, 19 (1). pp. 163-170. ISSN 2502-4752 E-ISSN 2502-4760 |
| spellingShingle | Q Science (General) Mat Razi, Nurul Izzati Abdul Rahman, Abdul Wahab Kamaruddin, Norhaslinda Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) |
| title | Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) |
| title_full | Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) |
| title_fullStr | Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) |
| title_full_unstemmed | Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) |
| title_short | Detecting learning disabilities based on neuro-physiological interface of affect (NPIoA) |
| title_sort | detecting learning disabilities based on neuro-physiological interface of affect (npioa) |
| topic | Q Science (General) |
| url | http://irep.iium.edu.my/80698/ http://irep.iium.edu.my/80698/13/Detecting%20learning%20disabilities%20based%20on%20neuro-physiological%20interface%20of%20affect_fulltext.pdf http://irep.iium.edu.my/80698/14/80698_Detecting%20learning%20disabilities%20based%20on%20neuro-physiological%20interface%20of%20affect_SCOPUS.pdf |