Comparison of the ICA and PCA Methods in Correction of EEG Signal Artefacts

被引：0

作者：

Kaczorowska, Monika ^{[1
]}

Plechawska-Wojcik, Malgorzata ^{[1
]}

Tokovarov, Mikhail ^{[1
]}

Dmytruk, Roman ^{[1
]}

机构：

[1] Lublin Univ Technol, Fac Elect Engn & Comp Sci, Inst Comp Sci, Lublin, Poland

来源：

2017 10TH INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING (ATEE) | 2017年

关键词：

EEG signal; Principal Component Analysis; Independent Component Analysis; BLIND SEPARATION; REMOVAL;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The paper presents application and comparison of two methods based on the blind source separation problem: Principal Component Analysis (PCA) and Independent Component Analysis (ICA) as well as combining these methods. Both methods might be applied in the task of eliminating artefacts from the electroencefalography (EEG) signal. Such artefacts might cover eye-blinks, muscle artefacts etc. The case study described in the paper presents the results of correcting various kinds of artefacts using these methods and its comparison to manual artefact detection performed by an expert.

引用

页码：262 / 267

页数：6

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