نوع مقاله : مقاله کامل پژوهشی
1 کارشناسی ارشد، گروه مهندسی پزشکی، دانشکدهی مهندسی، دانشگاه بینالمللی امام رضا (ع)، مشهد، ایران
2 استادیار، گروه مهندسی پزشکی، دانشکدهی مهندسی، دانشگاه بینالمللی امام رضا (ع)، مشهد، ایران
3 دکتری، گروه مهندسی پزشکی، دانشکدهی مهندسی، دانشگاه بینالمللی امام رضا (ع)، مشهد، ایران
اختلال کمتوجهی/بیشفعالی (ADHD) یک اختلال رشدی عصبی است که میتواند در افراد با سنین مختلف به خصوص در کودکان ایجاد شده و سبب تغییر در رفتار آنها شود. مطالعات گذشته اغلب روی پردازشهای حوزهی فرکانسی و یا جنبههای دینامیک غیرخطی سیگنالهای EEG از قبیل بعد همبستگی، بعد فرکتال، نمای لیاپانوف، آنتروپی و نرخ بازگشت فرایندهای مغزی برای تفکیک افراد مبتلا به ADHD متمرکز بوده است. در این مطالعه با استفاده از قطاعهای شعاعی پوانکاره در فضای فاز سیگنالهای EEG افراد مبتلا به ADHD و افراد سالم در دو گروه خردسالان و بزرگسالان، مرتبسازی این فضا و همچنین استخراج ویژگیهای هندسی مختلف، دیدگاه متفاوتی از میزان پیچیدگی فعالیتهای مغزی و سطح پویایی افراد مبتلا به ADHD در مقایسه با افراد سالم ارائه شده و به ارزیابی حجم بستر نوسان سیگنال EEG پرداخته شده است. در نهایت با ارزیابی ویژگیهای استخراج شده و استفاده از الگوریتم SFS بر مبنای طبقهبندی کنندهی RBF-SVM، تفکیک افراد مبتلا به ADHD از افراد سالم در دو گروه خردسالان و بزرگسالان به ترتیب با صحت 04/2±20/93 و 13/1±60/95 انجام شده است. نتایج این تحقیق نشان داده که حجم بستر نوسان سیگنال EEG افراد مبتلا به ADHD نسبت به افراد سالم به طور قابل توجهی بیشتر بوده و این موضوع بیانگر افزایش میزان پویایی و در نتیجه کاهش میزان پیچیدگی فعالیتهای مغزی در این افراد است. همچنین در این پژوهش مشخص شده که افزایش حجم بستر نوسان سیگنالهای EEG در کودکان نسبت به بزرگسالان بیشتر بوده و این موضوع نشان دهندهی افزایش سطح پویایی کودکان نسبت به بزرگسالان است. بنابراین میتوان ADHD و سن را به عنوان دو عامل مهم در افزایش حجم بستر نوسان سیگنال EEG معرفی کرد.
عنوان مقاله [English]
Separating the Healthy and ADHD People in Childhood and Adulthood using the EEG Phase Space Sorted by the Radial Poincare Sections
- Behnaz Sheikholeslami 1
- Ghasem Sadeghi Bajestani 2
- Reza Yaghoobi Karimui 3
- Reyhaneh Zarifiyan 1
1 M.Sc., Department of Medical Engineering, Faculty of Engineering, Imam Reza International University, Mashhad, Iran
2 Assistant Professor, Department of Medical Engineering, Faculty of Engineering, Imam Reza International University, Mashhad, Iran
3 Ph.D ., Department of Medical Engineering, Faculty of Engineering, Imam Reza International University, Mashhad, Iran
Attention Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that can affect people of all ages in the community, especially children, and cause changes in their behavior. Previous studies have often focused on frequency domain processing or the nonlinear dynamic aspects of EEG signals such as correlation dimension, fractal dimension, Lyapunov exponent, entropy, and recurrence rate of brain processes to differentiate individuals with ADHD. In this study, we evaluate the volume of the EEG signal oscillation basin using Poincare sections in the phase space of EEG signals of people with ADHD and healthy people and sort this space as well as extract various geometric features. We present a different perspective of complexity of brain activity and the level of dynamism of people with ADHD compared to healthy individuals. Finally, by evaluating the extracted features and using the SFS algorithm based on the RBF-SVM classifier, we were able to separate people with ADHD from healthy people in the groups of children and adults, with accuracy of 93.20±2.04 and 95.60±1.13. The results of this study showed that the volume of the EEG signal oscillation basin in people with ADHD was significantly higher than healthy people, which indicates an increase in the degree of dynamism and thus a decrease in the complexity of brain activity in these people. It was also identified in this study that the increase in the volume of the EEG signal oscillation basin in children is more than adults, which indicates an increase in the level of dynamism of children compared to adults. Therefore, ADHD and age can be introduced as two important factors in changing the volume of the EEG signal oscillation basin.
- Poincare Section
- Oscillation Basin
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