نوع مقاله : مقاله کامل پژوهشی

نویسندگان

1 استادیار، گروه مهندسی پزشکی، آزمایش‌گاه سیستم‌های سیبرنتیکی، دانشکده‌ی مهندسی، دانشگاه بین المللی امام رضا (ع)، مشهد

2 دانشجوی دکتری مهندسی پزشکی، گروه مهندسی پزشکی، دانشگاه شاهد، تهران

3 استاد، گروه بیوالکتریک، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی امیرکبیر، تهران

4 استاد، گروه مغز اطفال، بیمارستان قائم (عج)، دانشگاه علوم پزشکی مشهد، مشهد

چکیده

 اختلال اوتیسم یا درخودماندگی ذهنی یکی از اختلالات رایج بین کودکان است که با وجود تلاش‌های بسیار، هنوز هم تشخیص دقیق آن با روش‌های پاراکلینیکی ممکن نیست، از طرف دیگر، تشخیص زودهنگام این اختلال قبل از 18 ماهگی نقش به‌سزایی در اثر بخشی روش‌های درمانی بر این کودکان دارد. در این تحقیق، فضای جدیدی برای کمی‌سازی کیفیت تعاملات مغزی ارائه شده است که آن را فضای قبض و بسط (SFS) می­نامیم، این فضا مبتنی بر نگرش سیبرنتیک، کل­نگر و اطلاعاتی به سیگنال است. پس از انتقال سیگنال الکتروانسفالوگراف (EEG) به SFS برای 60 کودک نرمال و 60 کودک درخودمانده‌ی ذهنی در رنج سنی 3 تا 10 سال، با توجه به نگرش سیبرنتیک، در استخراج ویژگی نیز هر کودک با خودش در دو وضعیت مشاهده‌ی انیمیشن با صدا و بدون صدا مقایسه گردیده است و تفاوت تفاوت‌ها مورد بررسی قرار گرفته است. نتایج اعمال آزمون‌های آماری حاکی از معناداری بسیار زیاد (P-Value=1.4E-4) ویژگی‌های کیفی استخراج شده در تشخیص تغییر الگوی سالم و درخودمانده‌ی ذهنی است.

کلیدواژه‌ها

عنوان مقاله [English]

Detection of EEG Dynamic Pattern Variations based on Stretching-Folding Space Transportation (SFST) in Autism Spectrum Disorder

نویسندگان [English]

  • Ghasem Sadeghi Bajestani 1
  • Abbas Monzavi 2
  • Seyed Mohammad Reza Hashemi Golpayegani 3
  • Farah Ashrafzadeh 4

1 Assistant Professor, Research Center for Computational Cognitive Neuroscience, System & Cybernetic Labratory, Imam Reza International University, Mashhad, Iran

2 PhD Student, Biomedical Engineering Department, Shahed University, Tehran, Iran

3 Professor, Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran

4 Professor, Pediatrics Neurology Division, Ghaem Hospital, Mashhad University of Medical Sciences, Mashhad, Iran

چکیده [English]

Autism spectrum disorder (ASD) is a common disorder among children which despite painstakingly effort, it is not yet possible to be precisely detected using paraclinical methods. On the other hand, early detection, before 18th month, has pivotal role in treatment procedure. In this study, we present a method for early diagnosis of ASD based on the qualitative analysis of the Electroencephalogram (EEG) signal. We develop a new domain for quantifying the quality of interaction is present. We name it 'stretching – folding space’ (SFS). This domain is based on cybernetics, holistic and information-based analysis approaches. Therefore, it provides a non-deterministic approach to the biosignals. We collected data from 60 normal and 60 children with ASD in the range of 3-10 years old. We extracted features from the data in the SFS domain. The design of the study is self-controlled, meaning that each child serves as his/her own control. Each subject in the study watched a cartoon with and without sound, and the EEG signals were recorded. Statistical tests are applied on the extracted qualitative features in the SFS domain. The difference between the features of the data for each group (normal and ASD) was extracted, and the difference were compared between the groups. The results indicate that there is a statistically significant difference between the SFS features of normal and autism children. We conclude that our proposed method can serve as a new signal processing tool for diagnosing autism.

کلیدواژه‌ها [English]

  • Autism Spectrum Disorder
  • Stretching Folding Coefficient
  • Correlation Dimension
  • Trajectory
  • Phase Space
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