An EEG-based brain-computer interface with real-time artifact removal using independent component analysis

Chiu Kuo Chen; Ericson Chua; Zong Han Hsieh; Wai-Chi  Fang; Yu Te Wang; Tzyy Ping Jung

doi:10.1109/ICCE-Berlin.2012.6336491

An EEG-based brain-computer interface with real-time artifact removal using independent component analysis

Chiu Kuo Chen^*, Ericson Chua, Zong Han Hsieh, Wai-Chi Fang, Yu Te Wang, Tzyy Ping Jung

^*Corresponding author for this work

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

3 Scopus citations

Abstract

This paper presents a steady-state visually evoked potential (SSEVP) EEG-based brain-computer interface (BCI) with real-time artifact removal using independent component analysis (ICA). This system comprises an SSEVP-based stimulator, a four-channel electroencephalogram (EEG) front-end module, an ICA-based artifact removal module, and a canonical correlation analysis (CCA) detection module. The proposed SSEVP-based BCI system with artifact removal module is implemented and verified using ARM-based system on chip platform. The test patterns of 9Hz and 10Hz SSEVP raw data with a 2-second window, advancing with a 1-sec interval, are applied to this system, and the improvements of the hit rate are achieved approximately 53% and 48%, respectively.

Original language	English
Title of host publication	Proceedings 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Conference Proceedings
Pages	13-14
Number of pages	2
DOIs	https://doi.org/10.1109/ICCE-Berlin.2012.6336491
State	Published - 14 Dec 2012
Event	2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Berlin, Germany Duration: 3 Sep 2012 → 5 Sep 2012

Publication series

Name	IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
ISSN (Print)	2166-6814
ISSN (Electronic)	2166-6822

Conference

Conference	2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012
Country/Territory	Germany
City	Berlin
Period	3/09/12 → 5/09/12

Keywords

Artifact Removal
brain electroencephalogram (EEG)
independent component analysis (ICA)
InfoMax ICA component
Portable Brain Monitoring System

Access to Document

10.1109/ICCE-Berlin.2012.6336491

Cite this

Chen, C. K., Chua, E., Hsieh, Z. H., Fang, W-C., Wang, Y. T., & Jung, T. P. (2012). An EEG-based brain-computer interface with real-time artifact removal using independent component analysis. In Proceedings 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Conference Proceedings (pp. 13-14). Article 6336491 (IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin). https://doi.org/10.1109/ICCE-Berlin.2012.6336491

Chen, Chiu Kuo ; Chua, Ericson ; Hsieh, Zong Han et al. / An EEG-based brain-computer interface with real-time artifact removal using independent component analysis. Proceedings 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Conference Proceedings. 2012. pp. 13-14 (IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin).

@inproceedings{267a8b4648c545ec9703a286f073e337,

title = "An EEG-based brain-computer interface with real-time artifact removal using independent component analysis",

abstract = "This paper presents a steady-state visually evoked potential (SSEVP) EEG-based brain-computer interface (BCI) with real-time artifact removal using independent component analysis (ICA). This system comprises an SSEVP-based stimulator, a four-channel electroencephalogram (EEG) front-end module, an ICA-based artifact removal module, and a canonical correlation analysis (CCA) detection module. The proposed SSEVP-based BCI system with artifact removal module is implemented and verified using ARM-based system on chip platform. The test patterns of 9Hz and 10Hz SSEVP raw data with a 2-second window, advancing with a 1-sec interval, are applied to this system, and the improvements of the hit rate are achieved approximately 53% and 48%, respectively.",

keywords = "Artifact Removal, brain electroencephalogram (EEG), independent component analysis (ICA), InfoMax ICA component, Portable Brain Monitoring System",

author = "Chen, {Chiu Kuo} and Ericson Chua and Hsieh, {Zong Han} and Wai-Chi Fang and Wang, {Yu Te} and Jung, {Tzyy Ping}",

year = "2012",

month = dec,

day = "14",

doi = "10.1109/ICCE-Berlin.2012.6336491",

language = "English",

isbn = "9781467315470",

series = "IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin",

pages = "13--14",

booktitle = "Proceedings 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Conference Proceedings",

note = "2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 ; Conference date: 03-09-2012 Through 05-09-2012",

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Chen, CK, Chua, E, Hsieh, ZH, Fang, W-C, Wang, YT & Jung, TP 2012, An EEG-based brain-computer interface with real-time artifact removal using independent component analysis. in Proceedings 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Conference Proceedings., 6336491, IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin, pp. 13-14, 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012, Berlin, Germany, 3/09/12. https://doi.org/10.1109/ICCE-Berlin.2012.6336491

An EEG-based brain-computer interface with real-time artifact removal using independent component analysis. / Chen, Chiu Kuo; Chua, Ericson; Hsieh, Zong Han et al.
Proceedings 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Conference Proceedings. 2012. p. 13-14 6336491 (IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin).

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

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AU - Chen, Chiu Kuo

AU - Chua, Ericson

AU - Hsieh, Zong Han

AU - Fang, Wai-Chi

AU - Wang, Yu Te

AU - Jung, Tzyy Ping

PY - 2012/12/14

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N2 - This paper presents a steady-state visually evoked potential (SSEVP) EEG-based brain-computer interface (BCI) with real-time artifact removal using independent component analysis (ICA). This system comprises an SSEVP-based stimulator, a four-channel electroencephalogram (EEG) front-end module, an ICA-based artifact removal module, and a canonical correlation analysis (CCA) detection module. The proposed SSEVP-based BCI system with artifact removal module is implemented and verified using ARM-based system on chip platform. The test patterns of 9Hz and 10Hz SSEVP raw data with a 2-second window, advancing with a 1-sec interval, are applied to this system, and the improvements of the hit rate are achieved approximately 53% and 48%, respectively.

AB - This paper presents a steady-state visually evoked potential (SSEVP) EEG-based brain-computer interface (BCI) with real-time artifact removal using independent component analysis (ICA). This system comprises an SSEVP-based stimulator, a four-channel electroencephalogram (EEG) front-end module, an ICA-based artifact removal module, and a canonical correlation analysis (CCA) detection module. The proposed SSEVP-based BCI system with artifact removal module is implemented and verified using ARM-based system on chip platform. The test patterns of 9Hz and 10Hz SSEVP raw data with a 2-second window, advancing with a 1-sec interval, are applied to this system, and the improvements of the hit rate are achieved approximately 53% and 48%, respectively.

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KW - brain electroencephalogram (EEG)

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Chen CK, Chua E, Hsieh ZH, Fang W-C, Wang YT, Jung TP. An EEG-based brain-computer interface with real-time artifact removal using independent component analysis. In Proceedings 2012 IEEE 2nd International Conference on Consumer Electronics - Berlin, ICCE 2012 - Conference Proceedings. 2012. p. 13-14. 6336491. (IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin). doi: 10.1109/ICCE-Berlin.2012.6336491

An EEG-based brain-computer interface with real-time artifact removal using independent component analysis

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