Characterizing autistic disorder based on principle component analysis
Autism is often diagnosed during preschool or toddled age. This diagnosis often depends on behavioral test. It is known that individuals with autism have abnormal brain signals different from typical persons yet this difference in signals is slight that it is often difficult to distinguish from the...
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| Format: | Article |
| Language: | English |
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INSI Publications
2012
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| Online Access: | http://irep.iium.edu.my/22986/ http://irep.iium.edu.my/22986/1/Characterizing_autistic_disorder_based_on_principle_component_analysis.pdf |
| _version_ | 1848779086568095744 |
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| author | Shams, Wafa Khazal Abdul Rahman, Abdul Wahab |
| author_facet | Shams, Wafa Khazal Abdul Rahman, Abdul Wahab |
| author_sort | Shams, Wafa Khazal |
| building | IIUM Repository |
| collection | Online Access |
| description | Autism is often diagnosed during preschool or toddled age. This diagnosis often depends on behavioral test. It is known that individuals with autism have abnormal brain signals different from typical persons yet this difference in signals is slight that it is often difficult to distinguish from the normal. However, Electroencephalogram (EEG) signals have a lot of information which reflect the behavior of brain functions which therefore captures the marker for autism, help to early diagnose and speed the treatment. This work investigates and compares classification process for autism in open eyed tasks and motor movement by using Principle Component Analysis (PCA) for feature extracted in
Time-frequency domain to reduce data dimension. The results show that the proposed method gives accuracy in the range 90-100% for autism and normal children in motor task and around 90% to detect normal in open-eyed tasks though difficult to detect autism in this task. |
| first_indexed | 2025-11-14T15:12:11Z |
| format | Article |
| id | iium-22986 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T15:12:11Z |
| publishDate | 2012 |
| publisher | INSI Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-229862012-06-15T02:35:29Z http://irep.iium.edu.my/22986/ Characterizing autistic disorder based on principle component analysis Shams, Wafa Khazal Abdul Rahman, Abdul Wahab QA75 Electronic computers. Computer science Autism is often diagnosed during preschool or toddled age. This diagnosis often depends on behavioral test. It is known that individuals with autism have abnormal brain signals different from typical persons yet this difference in signals is slight that it is often difficult to distinguish from the normal. However, Electroencephalogram (EEG) signals have a lot of information which reflect the behavior of brain functions which therefore captures the marker for autism, help to early diagnose and speed the treatment. This work investigates and compares classification process for autism in open eyed tasks and motor movement by using Principle Component Analysis (PCA) for feature extracted in Time-frequency domain to reduce data dimension. The results show that the proposed method gives accuracy in the range 90-100% for autism and normal children in motor task and around 90% to detect normal in open-eyed tasks though difficult to detect autism in this task. INSI Publications 2012-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/22986/1/Characterizing_autistic_disorder_based_on_principle_component_analysis.pdf Shams, Wafa Khazal and Abdul Rahman, Abdul Wahab (2012) Characterizing autistic disorder based on principle component analysis. Australian Journal of Basic and Applied Sciences, 6 (1). pp. 149-155. ISSN 1991-8178 http://www.insipub.com/ajbas/2012/January/149-155.pdf |
| spellingShingle | QA75 Electronic computers. Computer science Shams, Wafa Khazal Abdul Rahman, Abdul Wahab Characterizing autistic disorder based on principle component analysis |
| title | Characterizing autistic disorder based on principle component analysis |
| title_full | Characterizing autistic disorder based on principle component analysis |
| title_fullStr | Characterizing autistic disorder based on principle component analysis |
| title_full_unstemmed | Characterizing autistic disorder based on principle component analysis |
| title_short | Characterizing autistic disorder based on principle component analysis |
| title_sort | characterizing autistic disorder based on principle component analysis |
| topic | QA75 Electronic computers. Computer science |
| url | http://irep.iium.edu.my/22986/ http://irep.iium.edu.my/22986/ http://irep.iium.edu.my/22986/1/Characterizing_autistic_disorder_based_on_principle_component_analysis.pdf |