Removal of EOG artifacts using ICA regression method

Ng Siew Cheok; P. Raveendran

doi:10.1007/978-3-540-69139-6_59

Removal of EOG artifacts using ICA regression method

Ng Siew Cheok, P. Raveendran

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

15 Citations (Scopus)

Abstract

The present study shows a hybrid method of removing Electrooculogram (EOG) artifacts. The Independent Component Analysis (ICA) method is used in conjunction with the regression method. The ICA estimates the EOG recordings from the Electroencephalogram (EEG) channels to be used to compute the propagation coefficients for the regression method. This ICA regression method is applied on to a set of EOG contaminated EEG signals. The result is compared to the typical regression method. It was found that the ICA regression method performs better than the typical regression method in removing artifacts especially the ones that contain eye blinks.

Original language	English
Title of host publication	4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008
Publisher	Springer
Pages	226-229
Number of pages	4
ISBN (Print)	9783540691389
DOIs	https://doi.org/10.1007/978-3-540-69139-6_59
Publication status	Published - 2008
Externally published	Yes
Event	Kuala Lumpur International Conference on Biomedical Engineering (BIOMED) 2008 - Kuala Lumpur, Malaysia Duration: 25 Jun 2008 → 28 Jun 2008 Conference number: 4th https://link.springer.com/book/10.1007/978-3-540-69139-6 (Proceedings)

Publication series

Name	IFMBE Proceedings
Number	1
Volume	21 IFMBE
ISSN (Print)	1680-0737

Conference

Conference	Kuala Lumpur International Conference on Biomedical Engineering (BIOMED) 2008
Abbreviated title	BIOMED 2008
Country/Territory	Malaysia
City	Kuala Lumpur
Period	25/06/08 → 28/06/08
Internet address	https://link.springer.com/book/10.1007/978-3-540-69139-6 (Proceedings)

Keywords

EEG
EOG
ICA
PCA
Regression

Access to Document

10.1007/978-3-540-69139-6_59

Cite this

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title = "Removal of EOG artifacts using ICA regression method",

abstract = "The present study shows a hybrid method of removing Electrooculogram (EOG) artifacts. The Independent Component Analysis (ICA) method is used in conjunction with the regression method. The ICA estimates the EOG recordings from the Electroencephalogram (EEG) channels to be used to compute the propagation coefficients for the regression method. This ICA regression method is applied on to a set of EOG contaminated EEG signals. The result is compared to the typical regression method. It was found that the ICA regression method performs better than the typical regression method in removing artifacts especially the ones that contain eye blinks.",

keywords = "EEG, EOG, ICA, PCA, Regression",

author = "\{Siew Cheok\}, Ng and P. Raveendran",

year = "2008",

doi = "10.1007/978-3-540-69139-6\_59",

language = "English",

isbn = "9783540691389",

series = "IFMBE Proceedings",

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number = "1",

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booktitle = "4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008",

address = "Switzerland",

note = "Kuala Lumpur International Conference on Biomedical Engineering (BIOMED) 2008<br/>, BIOMED 2008 ; Conference date: 25-06-2008 Through 28-06-2008",

url = "https://link.springer.com/book/10.1007/978-3-540-69139-6",

}

Siew Cheok, N & Raveendran, P 2008, Removal of EOG artifacts using ICA regression method. in 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008. IFMBE Proceedings, no. 1, vol. 21 IFMBE, Springer, pp. 226-229, Kuala Lumpur International Conference on Biomedical Engineering (BIOMED) 2008
, Kuala Lumpur, Malaysia, 25/06/08. https://doi.org/10.1007/978-3-540-69139-6_59

TY - GEN

T1 - Removal of EOG artifacts using ICA regression method

AU - Siew Cheok, Ng

AU - Raveendran, P.

N1 - Conference code: 4th

PY - 2008

Y1 - 2008

N2 - The present study shows a hybrid method of removing Electrooculogram (EOG) artifacts. The Independent Component Analysis (ICA) method is used in conjunction with the regression method. The ICA estimates the EOG recordings from the Electroencephalogram (EEG) channels to be used to compute the propagation coefficients for the regression method. This ICA regression method is applied on to a set of EOG contaminated EEG signals. The result is compared to the typical regression method. It was found that the ICA regression method performs better than the typical regression method in removing artifacts especially the ones that contain eye blinks.

AB - The present study shows a hybrid method of removing Electrooculogram (EOG) artifacts. The Independent Component Analysis (ICA) method is used in conjunction with the regression method. The ICA estimates the EOG recordings from the Electroencephalogram (EEG) channels to be used to compute the propagation coefficients for the regression method. This ICA regression method is applied on to a set of EOG contaminated EEG signals. The result is compared to the typical regression method. It was found that the ICA regression method performs better than the typical regression method in removing artifacts especially the ones that contain eye blinks.

KW - EEG

KW - EOG

KW - ICA

KW - PCA

KW - Regression

UR - https://www.scopus.com/pages/publications/77949617143

U2 - 10.1007/978-3-540-69139-6_59

DO - 10.1007/978-3-540-69139-6_59

M3 - Conference Paper

AN - SCOPUS:77949617143

SN - 9783540691389

T3 - IFMBE Proceedings

SP - 226

EP - 229

BT - 4th Kuala Lumpur International Conference on Biomedical Engineering 2008, Biomed 2008

PB - Springer

T2 - Kuala Lumpur International Conference on Biomedical Engineering (BIOMED) 2008<br/>

Y2 - 25 June 2008 through 28 June 2008

ER -

Removal of EOG artifacts using ICA regression method

Abstract

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Conference

Keywords

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