Filter-bank local region complex-valued common spatial pattern for Motor imagery classification

Yongkoo Park; Wonzoo Chung

doi:10.1109/BCI48061.2020.9061619

Filter-bank local region complex-valued common spatial pattern for Motor imagery classification

Yongkoo Park, Wonzoo Chung

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

3 Citations (Scopus)

Abstract

This paper represents a novel motor-imagery (MI) classification method based on a local region filter-bank common spatial pattern (LRFBCSP) using complexed form of electroencephalography (EEG) signals. LRFBCSP approach selects the MI-relevant local region which is constructed by individual channels and their neighbors by comparing their eigenvalue disparity. We propose an extension version of the LRFBCSP by considering the complex-valued spatial filtering rather than the real-valued spatial filtering. The complex-valued spatial filtering improves the discrimination of each local region and provides enhanced CSP features. Simulation result shows the performance improvement of the proposed method for BCI competition III dataset IVa by comparing the CSP-based methods.

Original language	English
Title of host publication	8th International Winter Conference on Brain-Computer Interface, BCI 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728147079
DOIs	https://doi.org/10.1109/BCI48061.2020.9061619
Publication status	Published - 2020 Feb
Event	8th International Winter Conference on Brain-Computer Interface, BCI 2020 - Gangwon, Korea, Republic of Duration: 2020 Feb 26 → 2020 Feb 28

Publication series

Name	8th International Winter Conference on Brain-Computer Interface, BCI 2020

Conference

Conference	8th International Winter Conference on Brain-Computer Interface, BCI 2020
Country/Territory	Korea, Republic of
City	Gangwon
Period	20/2/26 → 20/2/28

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was partly supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00432, Development of non-invasive integrated BCI SW platform to control home appliances and external devices by user’s thought via AR/VR interface) and Institute for Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Technology for Recognizing User’s Intentions using Deep Learning).

Keywords

Bain-computer interfaces (BCIs)
common spatial pattern (CSP)
component
electroencephalography (EEG)

ASJC Scopus subject areas

Behavioral Neuroscience
Cognitive Neuroscience
Artificial Intelligence
Human-Computer Interaction

Access to Document

10.1109/BCI48061.2020.9061619

Cite this

Park, Y., & Chung, W. (2020). Filter-bank local region complex-valued common spatial pattern for Motor imagery classification. In 8th International Winter Conference on Brain-Computer Interface, BCI 2020 Article 9061619 (8th International Winter Conference on Brain-Computer Interface, BCI 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BCI48061.2020.9061619

Filter-bank local region complex-valued common spatial pattern for Motor imagery classification. / Park, Yongkoo; Chung, Wonzoo.
8th International Winter Conference on Brain-Computer Interface, BCI 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9061619 (8th International Winter Conference on Brain-Computer Interface, BCI 2020).

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

Park, Y & Chung, W 2020, Filter-bank local region complex-valued common spatial pattern for Motor imagery classification. in 8th International Winter Conference on Brain-Computer Interface, BCI 2020., 9061619, 8th International Winter Conference on Brain-Computer Interface, BCI 2020, Institute of Electrical and Electronics Engineers Inc., 8th International Winter Conference on Brain-Computer Interface, BCI 2020, Gangwon, Korea, Republic of, 20/2/26. https://doi.org/10.1109/BCI48061.2020.9061619

Park Y, Chung W. Filter-bank local region complex-valued common spatial pattern for Motor imagery classification. In 8th International Winter Conference on Brain-Computer Interface, BCI 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 9061619. (8th International Winter Conference on Brain-Computer Interface, BCI 2020). doi: 10.1109/BCI48061.2020.9061619

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note = "Funding Information: ACKNOWLEDGMENT This work was partly supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00432, Development of non-invasive integrated BCI SW platform to control home appliances and external devices by user{\textquoteright}s thought via AR/VR interface) and Institute for Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00451, Development of BCI based Brain and Cognitive Computing Technology for Recognizing User{\textquoteright}s Intentions using Deep Learning).; 8th International Winter Conference on Brain-Computer Interface, BCI 2020 ; Conference date: 26-02-2020 Through 28-02-2020",

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AB - This paper represents a novel motor-imagery (MI) classification method based on a local region filter-bank common spatial pattern (LRFBCSP) using complexed form of electroencephalography (EEG) signals. LRFBCSP approach selects the MI-relevant local region which is constructed by individual channels and their neighbors by comparing their eigenvalue disparity. We propose an extension version of the LRFBCSP by considering the complex-valued spatial filtering rather than the real-valued spatial filtering. The complex-valued spatial filtering improves the discrimination of each local region and provides enhanced CSP features. Simulation result shows the performance improvement of the proposed method for BCI competition III dataset IVa by comparing the CSP-based methods.

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Filter-bank local region complex-valued common spatial pattern for Motor imagery classification

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this