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

doi:10.1109/IWW-BCI.2013.6506642

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 proceeding › Conference contribution

3 Citations (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 language	English
Title of host publication	2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
Pages	92-94
Number of pages	3
DOIs	https://doi.org/10.1109/IWW-BCI.2013.6506642
Publication status	Published - 2013
Event	2013 International Winter Workshop on Brain-Computer Interface, BCI 2013 - Gangwon Province, Korea, Republic of Duration: 2013 Feb 18 → 2013 Feb 20

Publication series

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

Other

Other	2013 International Winter Workshop on Brain-Computer Interface, BCI 2013
Country/Territory	Korea, Republic of
City	Gangwon Province
Period	13/2/18 → 13/2/20

Keywords

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

ASJC Scopus subject areas

Human-Computer Interaction

Access to Document

10.1109/IWW-BCI.2013.6506642

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). Article 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 et al.
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 proceeding › Conference 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, 13/2/18. https://doi.org/10.1109/IWW-BCI.2013.6506642

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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}",

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AU - Fazli, Siamac

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AU - Steinbrink, Jens

AU - Müller, Klaus Robert

AU - Lee, Seong Whan

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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.

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Multimodal imaging technique for rapid response brain-computer interface feedback

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Keywords

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