Multimodal imaging technique for rapid response brain-computer interface feedback

Seul Ki Yeom, Siamac Fazli, Jan Mehnert, Benjamin Blankcrtz, Jens Steinbrink, Klaus Robert Müller, Seong Whan Lee

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

1 Citation (Scopus)

Abstract

Electroencephalogram (EEG) has been widely used for brain-computer interface (BCI) due to its high temporal resolution. Meanwhile, multimodal imaging techniques based on combined EEG and near infrared spectroscopy (NIRS) have been studied in BCI research and shown to lead to beneficiary results in terms of classification [1]. However, performance results of this study show that there is a difference of peak accuracy (about 5s) between NIRS and EEG caused by the high latency of the NIRS signal. Based on our experimental results and analysis, we show that even though there is high latency of NIRS signal in our proposed multimodal imaging technique, it can be reasonable system for real-time BCI.

Original languageEnglish
Title of host publication2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
Pages92-94
Number of pages3
DOIs
Publication statusPublished - May 17 2013
Externally publishedYes
Event2013 International Winter Workshop on Brain-Computer Interface, BCI 2013 - Gangwon Province, Korea, Republic of
Duration: Feb 18 2013Feb 20 2013

Publication series

Name2013 International Winter Workshop on Brain-Computer Interface, BCI 2013

Other

Other2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
CountryKorea, Republic of
CityGangwon Province
Period2/18/132/20/13

Fingerprint

Brain computer interface
Near infrared spectroscopy
Electroencephalography
Feedback
Imaging techniques

Keywords

  • combined NIRS-EEG
  • hybrid BCI fast-paced NIRS
  • meta-classifier
  • multi-modal imaging

ASJC Scopus subject areas

  • Human-Computer Interaction

Cite this

Yeom, S. K., Fazli, S., Mehnert, J., Blankcrtz, B., Steinbrink, J., Müller, K. R., & Lee, S. W. (2013). Multimodal imaging technique for rapid response brain-computer interface feedback. In 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013 (pp. 92-94). [6506642] (2013 International Winter Workshop on Brain-Computer Interface, BCI 2013). https://doi.org/10.1109/IWW-BCI.2013.6506642

Multimodal imaging technique for rapid response brain-computer interface feedback. / Yeom, Seul Ki; Fazli, Siamac; Mehnert, Jan; Blankcrtz, Benjamin; Steinbrink, Jens; Müller, Klaus Robert; Lee, Seong Whan.

2013 International Winter Workshop on Brain-Computer Interface, BCI 2013. 2013. p. 92-94 6506642 (2013 International Winter Workshop on Brain-Computer Interface, BCI 2013).

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

Yeom, SK, Fazli, S, Mehnert, J, Blankcrtz, B, Steinbrink, J, Müller, KR & Lee, SW 2013, Multimodal imaging technique for rapid response brain-computer interface feedback. in 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013., 6506642, 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013, pp. 92-94, 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013, Gangwon Province, Korea, Republic of, 2/18/13. https://doi.org/10.1109/IWW-BCI.2013.6506642
Yeom SK, Fazli S, Mehnert J, Blankcrtz B, Steinbrink J, Müller KR et al. Multimodal imaging technique for rapid response brain-computer interface feedback. In 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013. 2013. p. 92-94. 6506642. (2013 International Winter Workshop on Brain-Computer Interface, BCI 2013). https://doi.org/10.1109/IWW-BCI.2013.6506642
Yeom, Seul Ki ; Fazli, Siamac ; Mehnert, Jan ; Blankcrtz, Benjamin ; Steinbrink, Jens ; Müller, Klaus Robert ; Lee, Seong Whan. / Multimodal imaging technique for rapid response brain-computer interface feedback. 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013. 2013. pp. 92-94 (2013 International Winter Workshop on Brain-Computer Interface, BCI 2013).
@inproceedings{61bb9aefd64c4e7aaf4c1e2fff7c8616,
title = "Multimodal imaging technique for rapid response brain-computer interface feedback",
abstract = "Electroencephalogram (EEG) has been widely used for brain-computer interface (BCI) due to its high temporal resolution. Meanwhile, multimodal imaging techniques based on combined EEG and near infrared spectroscopy (NIRS) have been studied in BCI research and shown to lead to beneficiary results in terms of classification [1]. However, performance results of this study show that there is a difference of peak accuracy (about 5s) between NIRS and EEG caused by the high latency of the NIRS signal. Based on our experimental results and analysis, we show that even though there is high latency of NIRS signal in our proposed multimodal imaging technique, it can be reasonable system for real-time BCI.",
keywords = "combined NIRS-EEG, hybrid BCI fast-paced NIRS, meta-classifier, multi-modal imaging",
author = "Yeom, {Seul Ki} and Siamac Fazli and Jan Mehnert and Benjamin Blankcrtz and Jens Steinbrink and M{\"u}ller, {Klaus Robert} and Lee, {Seong Whan}",
year = "2013",
month = "5",
day = "17",
doi = "10.1109/IWW-BCI.2013.6506642",
language = "English",
isbn = "9781467359733",
series = "2013 International Winter Workshop on Brain-Computer Interface, BCI 2013",
pages = "92--94",
booktitle = "2013 International Winter Workshop on Brain-Computer Interface, BCI 2013",

}

TY - GEN

T1 - Multimodal imaging technique for rapid response brain-computer interface feedback

AU - Yeom, Seul Ki

AU - Fazli, Siamac

AU - Mehnert, Jan

AU - Blankcrtz, Benjamin

AU - Steinbrink, Jens

AU - Müller, Klaus Robert

AU - Lee, Seong Whan

PY - 2013/5/17

Y1 - 2013/5/17

N2 - Electroencephalogram (EEG) has been widely used for brain-computer interface (BCI) due to its high temporal resolution. Meanwhile, multimodal imaging techniques based on combined EEG and near infrared spectroscopy (NIRS) have been studied in BCI research and shown to lead to beneficiary results in terms of classification [1]. However, performance results of this study show that there is a difference of peak accuracy (about 5s) between NIRS and EEG caused by the high latency of the NIRS signal. Based on our experimental results and analysis, we show that even though there is high latency of NIRS signal in our proposed multimodal imaging technique, it can be reasonable system for real-time BCI.

AB - Electroencephalogram (EEG) has been widely used for brain-computer interface (BCI) due to its high temporal resolution. Meanwhile, multimodal imaging techniques based on combined EEG and near infrared spectroscopy (NIRS) have been studied in BCI research and shown to lead to beneficiary results in terms of classification [1]. However, performance results of this study show that there is a difference of peak accuracy (about 5s) between NIRS and EEG caused by the high latency of the NIRS signal. Based on our experimental results and analysis, we show that even though there is high latency of NIRS signal in our proposed multimodal imaging technique, it can be reasonable system for real-time BCI.

KW - combined NIRS-EEG

KW - hybrid BCI fast-paced NIRS

KW - meta-classifier

KW - multi-modal imaging

UR - http://www.scopus.com/inward/record.url?scp=84877722285&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84877722285&partnerID=8YFLogxK

U2 - 10.1109/IWW-BCI.2013.6506642

DO - 10.1109/IWW-BCI.2013.6506642

M3 - Conference contribution

SN - 9781467359733

T3 - 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013

SP - 92

EP - 94

BT - 2013 International Winter Workshop on Brain-Computer Interface, BCI 2013

ER -