Hybrid brain-computer interface based on EEG and NIRS modalities

Min Ho Lee, Siamac Fazli, Jan Mehnert, Seong Whan Lee

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

10 Citations (Scopus)

Abstract

Non-invasive brain-computer interfaces (BCIs) allow users to control external devices by their intentions. Currently, most BCI systems are synchronous, which means, they rely on cues or tasks to which a subject has to react. It would be more useful for users if they could control a device at their own will (i.e., asynchronous BCIs). However, previous asynchronous BCI systems that rely on non-invasive electroencephalogram (EEG) measurements, are not accurate and stable enough for real world applications. Previously, hybrid BCI systems, relying on simultaneous EEG and near-infrared spectroscopy (NIRS) measurements, have been shown to increase the classification performance of synchronous motor imagery (MI) tasks. In this study, we present a first report on an asynchronous multi-modal hybrid BCI, based on simultaneous EEG and near-infrared spectroscopy (NIRS) measurements and propose novel subject-dependent classification strategies for combining both measurements.

Original languageEnglish
Title of host publication2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
PublisherIEEE Computer Society
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of
Duration: 2014 Feb 172014 Feb 19

Other

Other2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
CountryKorea, Republic of
CityGangwon
Period14/2/1714/2/19

Fingerprint

Brain computer interface
Near infrared spectroscopy
Electroencephalography
brain
Synchronous motors
user interface
performance

Keywords

  • Asynchronous BCI
  • Combined EEG-NIRS
  • Hybrid Brain-Computer Interface
  • Subject-dependent Classification

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Human Factors and Ergonomics

Cite this

Lee, M. H., Fazli, S., Mehnert, J., & Lee, S. W. (2014). Hybrid brain-computer interface based on EEG and NIRS modalities. In 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 [6782577] IEEE Computer Society. https://doi.org/10.1109/iww-BCI.2014.6782577

Hybrid brain-computer interface based on EEG and NIRS modalities. / Lee, Min Ho; Fazli, Siamac; Mehnert, Jan; Lee, Seong Whan.

2014 International Winter Workshop on Brain-Computer Interface, BCI 2014. IEEE Computer Society, 2014. 6782577.

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

Lee, MH, Fazli, S, Mehnert, J & Lee, SW 2014, Hybrid brain-computer interface based on EEG and NIRS modalities. in 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014., 6782577, IEEE Computer Society, 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014, Gangwon, Korea, Republic of, 14/2/17. https://doi.org/10.1109/iww-BCI.2014.6782577
Lee MH, Fazli S, Mehnert J, Lee SW. Hybrid brain-computer interface based on EEG and NIRS modalities. In 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014. IEEE Computer Society. 2014. 6782577 https://doi.org/10.1109/iww-BCI.2014.6782577
Lee, Min Ho ; Fazli, Siamac ; Mehnert, Jan ; Lee, Seong Whan. / Hybrid brain-computer interface based on EEG and NIRS modalities. 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014. IEEE Computer Society, 2014.
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