Rhythmic component extraction considering phase alignment and the application to motor imagery-based brain computer interfacing

Hiroshi Higashi, Toshihisa Tanaka, Yasue Mitsukura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

We propose a novel method for extracting a rhythmically oscillating signal from EEG recordings including multiple source signals which have similar frequencies. The main application of this method is brain computer interfaces (BCI), which use rhythmically oscillating signals such as alpha, mu, and beta waves, as feature signals. It is difficult to separate those components and/or extract an command-related component when these feature signals span the same frequency band. The main idea is to assume that signals generated in different brain parts have different phases, even though they have the same frequency. This hypothesis is effectively incorporated with the previously proposed rhythmic component extraction (RCE) method, which successfully extracts a signal oscillating at a certain frequency from multi-channel sensor signals in the BCI application. The signal model is firstly given and then this novel extraction method is formulated as an optimization problem. We apply the proposed method for the classification of multi-channel EEG signals between imaginary left/right hand movement. Our experiment suggests that the proposed method is effective in feature extraction for motor-imagery based BCI.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010 - Barcelona, Spain
Duration: 2010 Jul 182010 Jul 23

Other

Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
CountrySpain
CityBarcelona
Period10/7/1810/7/23

Fingerprint

Brain computer interface
Brain
Electroencephalography
Frequency bands
Feature extraction
Sensors
Experiments

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Rhythmic component extraction considering phase alignment and the application to motor imagery-based brain computer interfacing. / Higashi, Hiroshi; Tanaka, Toshihisa; Mitsukura, Yasue.

Proceedings of the International Joint Conference on Neural Networks. 2010. 5596476.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Higashi, H, Tanaka, T & Mitsukura, Y 2010, Rhythmic component extraction considering phase alignment and the application to motor imagery-based brain computer interfacing. in Proceedings of the International Joint Conference on Neural Networks., 5596476, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010, Barcelona, Spain, 10/7/18. https://doi.org/10.1109/IJCNN.2010.5596476
Higashi, Hiroshi ; Tanaka, Toshihisa ; Mitsukura, Yasue. / Rhythmic component extraction considering phase alignment and the application to motor imagery-based brain computer interfacing. Proceedings of the International Joint Conference on Neural Networks. 2010.
@inproceedings{806503ec40954140bb698f59c5c462d2,
title = "Rhythmic component extraction considering phase alignment and the application to motor imagery-based brain computer interfacing",
abstract = "We propose a novel method for extracting a rhythmically oscillating signal from EEG recordings including multiple source signals which have similar frequencies. The main application of this method is brain computer interfaces (BCI), which use rhythmically oscillating signals such as alpha, mu, and beta waves, as feature signals. It is difficult to separate those components and/or extract an command-related component when these feature signals span the same frequency band. The main idea is to assume that signals generated in different brain parts have different phases, even though they have the same frequency. This hypothesis is effectively incorporated with the previously proposed rhythmic component extraction (RCE) method, which successfully extracts a signal oscillating at a certain frequency from multi-channel sensor signals in the BCI application. The signal model is firstly given and then this novel extraction method is formulated as an optimization problem. We apply the proposed method for the classification of multi-channel EEG signals between imaginary left/right hand movement. Our experiment suggests that the proposed method is effective in feature extraction for motor-imagery based BCI.",
author = "Hiroshi Higashi and Toshihisa Tanaka and Yasue Mitsukura",
year = "2010",
doi = "10.1109/IJCNN.2010.5596476",
language = "English",
isbn = "9781424469178",
booktitle = "Proceedings of the International Joint Conference on Neural Networks",

}

TY - GEN

T1 - Rhythmic component extraction considering phase alignment and the application to motor imagery-based brain computer interfacing

AU - Higashi, Hiroshi

AU - Tanaka, Toshihisa

AU - Mitsukura, Yasue

PY - 2010

Y1 - 2010

N2 - We propose a novel method for extracting a rhythmically oscillating signal from EEG recordings including multiple source signals which have similar frequencies. The main application of this method is brain computer interfaces (BCI), which use rhythmically oscillating signals such as alpha, mu, and beta waves, as feature signals. It is difficult to separate those components and/or extract an command-related component when these feature signals span the same frequency band. The main idea is to assume that signals generated in different brain parts have different phases, even though they have the same frequency. This hypothesis is effectively incorporated with the previously proposed rhythmic component extraction (RCE) method, which successfully extracts a signal oscillating at a certain frequency from multi-channel sensor signals in the BCI application. The signal model is firstly given and then this novel extraction method is formulated as an optimization problem. We apply the proposed method for the classification of multi-channel EEG signals between imaginary left/right hand movement. Our experiment suggests that the proposed method is effective in feature extraction for motor-imagery based BCI.

AB - We propose a novel method for extracting a rhythmically oscillating signal from EEG recordings including multiple source signals which have similar frequencies. The main application of this method is brain computer interfaces (BCI), which use rhythmically oscillating signals such as alpha, mu, and beta waves, as feature signals. It is difficult to separate those components and/or extract an command-related component when these feature signals span the same frequency band. The main idea is to assume that signals generated in different brain parts have different phases, even though they have the same frequency. This hypothesis is effectively incorporated with the previously proposed rhythmic component extraction (RCE) method, which successfully extracts a signal oscillating at a certain frequency from multi-channel sensor signals in the BCI application. The signal model is firstly given and then this novel extraction method is formulated as an optimization problem. We apply the proposed method for the classification of multi-channel EEG signals between imaginary left/right hand movement. Our experiment suggests that the proposed method is effective in feature extraction for motor-imagery based BCI.

UR - http://www.scopus.com/inward/record.url?scp=79959472458&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79959472458&partnerID=8YFLogxK

U2 - 10.1109/IJCNN.2010.5596476

DO - 10.1109/IJCNN.2010.5596476

M3 - Conference contribution

SN - 9781424469178

BT - Proceedings of the International Joint Conference on Neural Networks

ER -