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Caspian Journal of Neurological Sciences، جلد ۱۰، شماره ۱، صفحات ۰-۰
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Artificial Neural Network in Autism Spectrum Disorder Diagnosis Based on Quantitative Electroencephalography |
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| چکیده انگلیسی مقاله |
Background: Early diagnosis of autism spectrum disorder (ASD) is essential because the challenges that ASD children and their parents face will be managed better by developmental and behavioral intervention at earlier ages.
Objectives: This study aims to diagnose ASD based on electroencephalography (EEG) with the help of an artificial neural network (ANN).
Materials & Methods: The statistical population includes all girls and boys aged 3 to 7 years referred to child psychiatry and neurodevelopmental centers in Mashhad City, Iran. A total of 34 children with ASD (5 girls and 29 boys) and 11 children without any neurodevelopmental disorders (8 girls and 3 boys) participated in this study. EEG signals were recorded through C3 and C4 channels based on the standard 10-20 system. With the help of programming codes, the absolute power of the frequency bands (delta, theta, alpha, mu rhythm, beta, and gamma) was extracted from the brain signals of the samples.
Results: This study showed a significant difference in mu rhythm between the two groups. The classification result based on discriminant function analysis in two groups gave a sensitivity of 67.6% in the third stage of EEG recording. Seven band frequencies were used as features for ANN inputs. The results indicated that the radial basis function network with 40± 2 neurons in the hidden layer accurately diagnosed and classified the EEG signals of ASD children from non-neurodevelopmental children (mean square error =1.22325e-5).
Conclusion: It can be concluded that band frequencies are notable features in diagnosing ASD.
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| کلیدواژه‌های انگلیسی مقاله |
Autism spectrum disorder, Electroencephalography, Diagnosis |
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| نویسندگان مقاله |
| Mitra Dadjoo
Exceptional Child Psychology and Education, University of Guilan, Rasht, Iran.
| Sajjad Rezaei
Department of Psychology, Faculty of Literature and Humanities, University of Guilan, Rasht, Iran.
| Kambiz Rohampour
Department of Physiology, School of Medicine, Guilan University of Medical Sciences, Guilan, Rasht, Iran.
| Ashkan Naseh
Department of Psychology, University of Guilan, Rasht, Iran
| Ghasem Sadeghi Bajestani
Biomedical Engineering, Imam Reza International University, Mashhad, Razavi Khorasan, Iran.
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| نشانی اینترنتی |
http://cjns.gums.ac.ir/browse.php?a_code=A-10-24-8&slc_lang=en&sid=1 |
| فایل مقاله |
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| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
تخصصی |
| نوع مقاله منتشر شده |
پژوهشی |
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