Bimodal BCI using simultaneously NIRS and EEG

Yohei Tomita, Francois Benoit Vialatte, Gerard Dreyfus, Yasue Mitsukura, Hovagim Bakardjian, Andrzej Cichocki

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

Although noninvasive brain-computer interfaces (BCI) based on electroencephalographic (EEG) signals have been studied increasingly over the recent decades, their performance is still limited in two important aspects. First, the difficulty of performing a reliable detection of BCI commands increases when EEG epoch length decreases, which makes high information transfer rates difficult to achieve. Second, the BCI system often misclassifies the EEG signals as commands, although the subject is not performing any task. In order to circumvent these limitations, the hemodynamic fluctuations in the brain during stimulation with steady-state visual evoked potentials (SSVEP) were measured using near-infrared spectroscopy (NIRS) simultaneously with EEG. BCI commands were estimated based on responses to a flickering checkerboard (ON-period). Furthermore, an 'idle' command was generated from the signal recorded by the NIRS system when the checkerboard was not flickering (OFF-period). The joint use of EEG and NIRS was shown to improve the SSVEP classification. For 13 subjects, the relative improvement in error rates obtained by using the NIRS signal, for nine classes including the 'idle' mode, ranged from 85% to 53%, when the epoch length increase from 3 to 12 s. These results were obtained from only one EEG and one NIRS channel. The proposed bimodal NIRS-EEG approach, including detection of the idle mode, may make current BCI systems faster and more reliable.

Original languageEnglish
Article number6714514
Pages (from-to)1274-1284
Number of pages11
JournalIEEE Transactions on Biomedical Engineering
Volume61
Issue number4
DOIs
Publication statusPublished - 2014

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Keywords

  • bimodal
  • Brain-computer interface (BCI)
  • simultaneous electroencephalographic (EEG) and near-infrared spectroscopy (NIRS)
  • steady-state visual evoked potentials (SSVEP)

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Tomita, Y., Vialatte, F. B., Dreyfus, G., Mitsukura, Y., Bakardjian, H., & Cichocki, A. (2014). Bimodal BCI using simultaneously NIRS and EEG. IEEE Transactions on Biomedical Engineering, 61(4), 1274-1284. [6714514]. https://doi.org/10.1109/TBME.2014.2300492