استخراج اطلاعات تفاضلی سیگنال‌های الکتروانسفالوگرام جهت تشخیص اختلال وسواس اجباری
الموضوعات : سامانه‌های پردازشی و ارتباطی چندرسانه‌ای هوشمندفرزانه منظری 1 , پیوند قادریان 2
1 - دانشجوی کارشناسی ارشد، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی سهند تبریز
2 - دانشکده مهندسی پزشکی، دانشگاه صنعتی سهند، تبریز، ایران
الکلمات المفتاحية: ویژگی‌های آماری تفاضلی, اختلال وسواس اجباری, تجزیه به مؤلفه‌های مد ذاتی, ماشین بردار پشتیبان,
ملخص المقالة :
اختلال وسواس اجباری یک بیماری مزمن ذهنی و اجتماعی است که در بین حدود 2 تا 3 درصد جمعیت انسان‌ها شیوع دارد و سبب مشکلاتی در عملکردهای شناختی و افت کیفیت زندگی مبتلایان می‌گردد. به همین علت تشخیص صحیح و به هنگام آن می‌تواند به روان پزشکان در درمان و یا کنترل این بیماری کمک کند. تحقیقات پیشین در زمینه‌ی بیماری وسواس اجباری نشان‌دهنده‌ی اختلال در فعالیت الکتریکی بین نواحی مختلف مغزی بوده‌اند. بنابراین، در این مطالعه رویکردی جدید در زمینه‌ی تشخیص اختلال وسواس اجباری ارائه شده است که مبتنی بر تجزیه سیگنال به توابع پایه‌ای ذاتی و استخراج تغییرات لحظه‌ای دامنه و فاز سیگنال الکتروانسفالوگرام به صورت تفاضلی در حین انجام تکالیف فلانکر می‌باشد. ارزیابی الگوریتم پیشنهادی با داده‌های الکتروانسفالوگرام 19 فرد سالم و 11 بیمار دارای اختلال وسواس اجباری توسط طبقه‌بند ماشین بردار پشتیبان صورت گرفته است. نتایج به دست آمده، قابلیت روش پیشنهادی در تشخیص بیماری را با صحت بالای 89/93 درصد با استفاده از اطلاعات تفاضلی دامنه‌ی سیگنال الکتروانسفالوگرام نشان داده‌اند. در مقایسه بین نواحی مختلف ویژگی‌های آماری مستخرج از لوب پیشانی، شبکه‌ی پیشانی-آهیانه و نیم‌کره‌ی مغزی کارایی بیشتری در تشخیص بیماری ارائه داده‌اند.
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