پیش‌بینی موفقیت در درمان نوروفیدبک برای بیماران اختلال نقص توجه و بیش‌فعالی پیش از شروع درمان

روش‌های هوشمند در صنعت برق

مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 10 اردیبهشت 1402   

نوع مقاله: مقاله پژوهشی

نویسندگان

نیکو خان احمدی¹؛ محمدرضا یوسفی^{* 2}

¹دانشکده مهندسی برق- واحد نجف‌آباد، دانشگاه آزاد اسلامی، نجف‌آباد، ایران

²دانشگاه آزاد اسلامی واحد نجف آباد

چکیده

نورفیدبک بهترین روش ارائه‌شده برای درمان اختلال نقص توجه و بیش فعالی به‌ویژه در کودکان است. در این مقاله روش پیش‌بینی درمان‌پذیری بیماران مبتلابه بیش‌فعالی با آموزش نوروفیدبک به کمک استخراج باند فرکانسی سیگنال EEG و با استفاده از معیار ارزیابی ارتباطات مغزی-عملکردی انجام‌شده تا قبل از شروع درمان نوروفیدبک درمان‌پذیری شخص تشخیص داده شود. این الگوریتم شامل چهار مرحله است: در گام اول یک مجموعه داده از ثبت سیگنال EEG حین تحریک نوروفیدبک از 60 دانش‌آموز در رده‌ سنی 7 تا 14 سال مبتلا به بیش‌فعالی در دو کلاس درمان‌پذیر و درمان‌ناپذیر از پایگاه داده مندلی دریافت ‌شده است. در گام بعدی فیلترینگ اولیه برای کاهش نویز مجموعه‌ داده‌ها با استفاده از یک بلوک پیش‌پردازش انجام ‌شده است. در گام سوم توزیع فرکانسی باند آلفا و بتا از سیگنال‌های کاهش نویز شده استخراج‌شده است. در این نوع داده تفاوت در اجزای EEG هر گروه با استفاده از سنجش ارتباطات مغزی-عملکردی و به کمک شاخص قفل فاز قابل‌بیان بوده که برای تشخیص وجود ارتباط بین لوب های مغزی درگیر یک‌بار با استفاده از شاخص مقدار احتمال در آزمون آماری تی تست و برای افزایش صحت، از الگوریتم ژنتیک برای تشخیص الکترودهای مؤثر در درمان استفاده ‌شده است. نتایج نشان میدهند که لوب‌های درگیر هنگام تحریک نوروفیدبک، لوب‌های فرونتال و سنترال هستند و از بین 32 کانال ثبت EEG فقط داده‌های مربوط به 6 کانال C3، FZ، F4، CZ، C4 و F3 تفاوت معناداری در میزان ارتباطات مغزی حین تحریک از خود نشان می دهند.

کلیدواژه‌ها

لکتروانسفالوگرام؛ الگوریتم ژنتیک؛ بیش‌فعالی؛ پیش‌بینی؛ شبکه‌ ارتباطات مغزی؛ نوروفیدبک

سایر فایل های مرتبط با مقاله

1896-Extended Abstract.pdf

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