A novel neural network with non-recursive IIR filters on EEG artifacts elimination

被引：1

作者：

Miyazaki, Ryota ^{[1
]}

Ohshiro, Masakuni ^{[1
]}

Nishimura, Toshihiro ^{[1
]}

Tsubai, Masayoshi ^{[1
]}

机构：

[1] Waseda Univ, Grad Sch Informat Prod & Syst, Wakamatsu Ku, Kitakyushu, Fukuoka 8080135, Japan

来源：

2005 27TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-7 | 2005年

关键词：

D O I：

10.1109/IEMBS.2005.1616860

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

The artifacts caused by various factors, EOG (electrooculogram), blink and EMG (electromyogram), in EEG (Electroencephalogram) signals increase the difficulty in analyzing them. In addition, EEG signals containing artifacts often cannot be used in analyzing them. So, it is useful and indispensable to eliminate the artifacts from EEG signals. In this paper, a neural network with non-recursive IIR (Infinite Impulse Response) filters are used to eliminate the artifacts from EEG signals. The proposed method is a new approach that is respect to slotting a non-recursive E[R filter into individual neurons of a neural network. First of all, in order to investigate the usefulness of the proposed method in eliminating the artifacts from EEG signals, we apply it to the artificial EEG signals that are weakly stationary process. As the result, the artifacts can be eliminated from EEG signals almost exactly using the proposed method, and it is suggested the proposed method should be useful in eliminating the artifacts from EEG signals.

引用

页码：2048 / 2051

页数：4