علوم رایانش و فناوری اطلاعات

آزمون دروغ‌سنجی مبتنی بر تلفیق اطلاعات آشوبناک کانال‌های سیگنال الکتروانسفالوگرام

نویسندگان

1 دانشجوی کارشناسی ارشد، دانشکده علوم و فناوری های نوین، دانشگاه سمنان، سمنان، ایران

2 استادیار، دانشکده علوم و فناوری های نوین، دانشگاه سمنان، سمنان، ایران

3 استادیار، دانشکده مهندسی پزشکی، دانشگاه صنعتی همدان، همدان، ایران

چکیده

در سال‌های اخیر استفاده از مؤلفه P300 در آزمون دانش گناهکار، از روش‌های پرکاربرد به شمار می‌رود. در مطالعات مختلف، کانال Pz  به عنوان کانال حاوی بیشترین اطلاعات مربوط به این مؤلفه شناخته شده‌است. با این وجود، پژوهش‌های دیگر نشان داده‌اند که کانال‌های Fz و Cz نیز اطلاعات مفیدی از مؤلفه‌ی P300  ارائه می‌دهند. بنابراین، حل چالش استفاده توأمان و بهینه از اطلاعات این سه کانال می‌تواند در بهبود نتایج حاصل از آزمون دروغ‌سنجی مؤثر واقع شود. در این مقاله به منظور استخراج اطلاعات مرتبط با مؤلفه P300، از تجزیه تحلیل کمّی بازرخداد سیگنال الکتروانسفالوگرام بهره گرفته شد. از سوی دیگر به منظور تلفیق اطلاعات آشوبناک این سه کانال، از رویکردهای تلفیق اطلاعات در سطح ویژگی و در سطح تصمیم‌گیری استفاده شد. برای تلفیق اطلاعات در سطح ویژگی دو روش (1) تلفیق تمامی ویژگی‌های سه کانال و تشکیل یک بردار کلی و (2) انتخاب ویژگی‌های بهینه از بردار مذکور با استفاده از الگوریتم ژنتیک مدنظر قرار گرفت. به منظور تلفیق اطلاعات در سطح تصمیم‌گیری نیز احتمال پسین وزن‌دار هر کلاس بر اساس بردارهای ویژگی و قابلیت اطمینان‌ هر کانال محاسبه شد و برای تشخیص افراد گناهکار و بی‌گناه مورد استفاده قرار گرفت. از میان رویکردهای پیشنهادی، رویکرد تلفیق اطلاعات در سطح تصمیم‌گیری با صحت 90 درصد، حساسیت 86/67 درصد و ویژه بودن 93/33 درصد نشان‌دهنده برتری این روش در قیاس با رویکردهای پیشنهادی دیگر است. علاوه بر این، سرعت اجرای پردازش‌های مربوط به این روش نسبت به روش مبتنی بر الگوریتم ژنتیک بسیار بالاتر است.

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علوم رایانش و فناوری اطلاعات
دوره 19، شماره 1
بهار و تابستان
اردیبهشت 1400