A Novel Deep Learning Approach for Recognizing Stereotypical Motor Movements within and across Subjects on the Autism Spectrum Disorder
المؤلفون المشاركون
Essoufi, EL-Hassan
Sadouk, Lamyaa
Gadi, Taoufiq
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-07-10
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by persistent difficulties including repetitive patterns of behavior known as stereotypical motor movements (SMM).
So far, several techniques have been implemented to track and identify SMMs.
In this context, we propose a deep learning approach for SMM recognition, namely, convolutional neural networks (CNN) in time and frequency-domains.
To solve the intrasubject SMM variability, we propose a robust CNN model for SMM detection within subjects, whose parameters are set according to a proper analysis of SMM signals, thereby outperforming state-of-the-art SMM classification works.
And, to solve the intersubject variability, we propose a global, fast, and light-weight framework for SMM detection across subjects which combines a knowledge transfer technique with an SVM classifier, therefore resolving the “real-life” medical issue associated with the lack of supervised SMMs per testing subject in particular.
We further show that applying transfer learning across domains instead of transfer learning within the same domain also generalizes to the SMM target domain, thus alleviating the problem of the lack of supervised SMMs in general.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sadouk, Lamyaa& Gadi, Taoufiq& Essoufi, EL-Hassan. 2018. A Novel Deep Learning Approach for Recognizing Stereotypical Motor Movements within and across Subjects on the Autism Spectrum Disorder. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1130829
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sadouk, Lamyaa…[et al.]. A Novel Deep Learning Approach for Recognizing Stereotypical Motor Movements within and across Subjects on the Autism Spectrum Disorder. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-16.
https://search.emarefa.net/detail/BIM-1130829
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sadouk, Lamyaa& Gadi, Taoufiq& Essoufi, EL-Hassan. A Novel Deep Learning Approach for Recognizing Stereotypical Motor Movements within and across Subjects on the Autism Spectrum Disorder. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-16.
https://search.emarefa.net/detail/BIM-1130829
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130829
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر