Automatic Removal of Ocular Artefacts In EEG Signal by Using Independent Component Analysis and Chauvenet Criterion

被引：0

作者：

Cinar, Salim ^{[1
]}

Acir, Nurettin ^{[2
]}

机构：

[1] Nigde Univ, Elekt Elekt Muhendisligi Bolumu, Nigde, Turkey

[2] Bursa Tekn Univ, Elekt Elekt Muhendisligi Bolumu, Bursa, Turkey

来源：

2016 MEDICAL TECHNOLOGIES NATIONAL CONFERENCE (TIPTEKNO) | 2015年

关键词：

ICA; removal of arefacts; Chauvenet criterion; NEURAL-NETWORK;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Eye movements (saccade, blink and cause artefacts in Electroencephalogram recordings. The ocular artefact can distort the EEG signals. Removal of ocular artefact is important issue in EEG signal analysis. The main task of artefact removal algorithms is to obtain cleaned EEG without losing meaningful EEG signal. The main focus of this work is to remove ocular artefact automatically by using Independent Component Analysis and Chauvenet criterion. The method is tested on real dataset. Relative error and Correlation coefficient are used for the performance test. The performance of the proposed method was Relative error= 0.273 +/- 0.148, Correlation coefficient= 0.943 +/- 0.042 in the dataset. The results show that the porposed method effectively removes ocular artefacts in EEG.

引用

页数：4

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