EEG Artifact Detection Using Spatial Distribution of Rhythmicity

被引：2

作者：

Skupch, A. M. ^{[1
]}

Dollfuss, P. ^{[1
]}

Fuerbass, F. ^{[1
]}

Hartmann, M. ^{[1
]}

Perko, H. ^{[1
]}

Pataraia, E. ^{[2
]}

Lindinger, G. ^{[2
]}

Kluge, T. ^{[1
]}

机构：

[1] Austrian Inst Technol, Donau City Str 1, A-1220 Vienna, Austria

[2] Med Univ Vienna, Dept Clin Neurol, Vienna, Austria

来源：

3RD INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND TECHNOLOGY - ICBET 2013 | 2013年 / 7卷

关键词：

artifacts; automatic seizure detection; EEG; rhythmicity;

D O I：

10.1016/j.apcbee.2013.08.005

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

The contamination of EEG by artifacts requires automatic artifact detection for EEG processing systems. It is particularly important for automatic seizure detection systems since artifacts can mimic rhythmical pathological EEG. In this paper we present a novel approach to artifact detection by considering the spatial distribution of the rhythmicity of the EEG signal with the help of the Periodic Waveform Analysis (PWA). The algorithm enables to identify defect electrodes during the EEG-processing. The good performance of this algorithm is shown by including it into the automatic seizure detection system EpiScan and applying it to a very large and varied database. (C) 2013 The Authors. Published by Elsevier B.V.

引用

页码：16 / 20

页数：5

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