A Novel Geometrical Method for Depression Diagnosis Based on EEG Signals

  • سال انتشار: 1398
  • محل انتشار: چهارمین کنفرانس ملی تکنولوژی در مهندسی برق و کامپیوتر
  • کد COI اختصاصی: ETECH04_071
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 793
دانلود فایل این مقاله

نویسندگان

Alireza Azizi

Department of Biomedical Engineering Faculty of health, Tehran Medical Sciences Islamic Azad University, Tehran, Iran

Mohammad Karimi Moridani

Department of Biomedical Engineering Faculty of health, Tehran Medical Sciences Islamic Azad University, Tehran, Iran

Abdolkarim Saeedi

Department of Biomedical Engineering Faculty of health, Tehran Medical Sciences Islamic Azad University, Tehran, Iran

چکیده

The aim of this study is to provide a low time consuming non-linear technique for short duration EEG signals, which are complex and non-linear in general. Forty subjects (20 depressed, 20 normals) were included in this study. EEG was recorded with a bipolar montage and a sampling frequency of 256HZ. Each recording consisted of a 5 min recording with eyes open and closed. One Thousand and five hundred samples were selected from each subject for further analysis. Several novel methods are proposed in this study: Centroid to Centroid Distance, Centroid to 45-degree line shortest Distance, Incenter Radius, all built on different aspects of distance in Cartesian space. Based on student s t-test all of the features were found statistically significant (p< 0.0001). The depressed group showed higher values in all features compared to the healthy group. Also, all of the features were more distinct in the right hemisphere. According to this study, the proposed methods are viable for diagnosis of depression in short-termed EEG signals.

کلیدواژه ها

Depression, EEG signals, Non-linear analysis, Geometric features, Statistical analysis

مقالات مرتبط جدید

اطلاعات بیشتر در مورد COI

COI مخفف عبارت CIVILICA Object Identifier به معنی شناسه سیویلیکا برای اسناد است. COI کدی است که مطابق محل انتشار، به مقالات کنفرانسها و ژورنالهای داخل کشور به هنگام نمایه سازی بر روی پایگاه استنادی سیویلیکا اختصاص می یابد.

کد COI به مفهوم کد ملی اسناد نمایه شده در سیویلیکا است و کدی یکتا و ثابت است و به همین دلیل همواره قابلیت استناد و پیگیری دارد.