Using NIRS as a predictor for EEG-based BCI performance.

Siamac Fazli, Jan Mehnert, Jens Steinbrink, Benjamin Blankertz

Research output: Contribution to journalArticle

18 Citations (Scopus)

Abstract

Multimodal recordings of EEG and NIRS of 14 subjects are analyzed in the context of sensory-motor based Brain Computer Interface (BCI). Our findings indicate that performance fluctuations of EEG-based BCI control can be predicted by preceding Near-Infrared Spectroscopy (NIRS) activity. These NIRS-based predictions are then employed to generate new, more robust EEG-based BCI classifiers, which enhance classification significantly, while at the same time minimize performance fluctuations and thus increase the general stability of BCI performance.

Original languageEnglish
Pages (from-to)4911-4914
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
Volume2012
Publication statusPublished - 2012 Dec 1
Externally publishedYes

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Brain-Computer Interfaces
Brain computer interface
Near infrared spectroscopy
Near-Infrared Spectroscopy
Electroencephalography
Classifiers

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

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