نوع مقاله: مقاله کامل پژوهشی

نویسندگان

1 کارشناس ارشد، دانشکده مهندسی پزشکی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی

2 استادیار، دانشکده مهندسی برق، دانشگاه علم و صنعت ایران،

3 استادیار، دانشکده مهندسی پزشکی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی

4 استاد، مرکز تحقیقات روانپزشکی بیمارستان روزبه، دانشگاه علوم پزشکی تهران

5 دانشیار، مرکز تحقیقات روانپزشکی بیمارستان روزبه، دانشگاه علوم پزشکی تهران

10.22041/ijbme.2010.13295

چکیده

در این مقاله، کاربرد تحلیل مؤلفه‌های مستقل (ICA) برای تشخیص بیماری اوتیسم مورد بررسی قرار گرفته است. ابتدا منابع تولید کننده سیگنال‌های EEGبا ICAاستخراج و سپس پردازش‌های حوزه زمان و فرکانس بر این مؤلفه‌های سیگنالی اعمال شدند. سیگنال‌های EEGاز 10 کودک مبتلا به اوتیسم و 10 کودک سالم در محدوده سنی 6-11 سال گرفته شده است. نتایج به کمک روش آماری آزمون تی با هم مقایسه شده‌اند. پائین‌تر بودن سطح همبستگی میان منابع نیم‌کره چپ مغز به ویژه ناحیه مربوط به کانال 3Cدر افراد مبتلا به اوتیسم نسبت به افراد سالم مشاهده شده است. همچنین میانگین انرژی باند فرکانسی تتا در منابع نیم‌کره چپ مغز به‌خصوص کانال‌های 3Cو 3Fبرای افراد مبتلا به اوتیسم نسبت به افراد سالم پائین‌تر بوده و این معیار در باند فرکانسی گاما بالاتر به دست آمده است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Evaluation of EEG Signal in Autism Disorder with ICA Analysis

نویسندگان [English]

  • Mohammad Rashidi 1
  • Hamid Behnam 2
  • Ali Sheikhani 3
  • Mohammad Reza Mohammadi 4
  • Maryam Norouzian 5

1 M.Sc Graduated, Bioelectric Group, School of Biomedical Engineering, Science and Research Branch, Islamic Azad University

2 Assistant Professor, Biomedical Engineering Group, School of Electrical Engineering, Iran University of Science and Technology

3 Assistant Professor, Bioelectric Group, School of Biomedical Engineering, Science and Research Branch, Islamic Azad University

4 Professor, Psychological Research center, Roozbeh Hospital, Medical Science University of Teharn

5 Associate Professor, Psychological Research center, Roozbeh Hospital, Medical Science University of Teharn

چکیده [English]

This paper presents ICA analysis application for detection of autism disorder. In the first step, resources of EEG signals were extracted by ICA and then time domain and frequency domain processing were implemented. EEG signals of ten children with autism and ten healthy children aged 6 to 11 years have been obtained. The results have been compared statistically by T-test. Lower correlation levels between resources of the left hemisphere of the brain especially C3 channel region in autistic children compared with healthy subjects have been observed. Also the average energy of theta frequency band in C3 and F3 channels for children with autism were lower than that in healthy people and this criterion was higher in gamma frequency band.

کلیدواژه‌ها [English]

  • Electroencephalography
  • Autism disorder
  • Independent component analysis
  • Correlation analysis
  • Spectrum energy

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