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Evaluating a four-class motor-imagery-based optical brain-computer interface
Conference proceeding

Evaluating a four-class motor-imagery-based optical brain-computer interface

Alyssa M Batula, Hasan Ayaz and Youngmoo E Kim
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, v 2014, pp 2000-2003
Aug 2014
PMID: 25570375

Abstract

Training Spectroscopy Accuracy Brain-computer interfaces Electroencephalography Hemodynamics Foot
This work investigates the potential of a four-class motor-imagery-based brain-computer interface (BCI) using functional near-infrared spectroscopy (fNIRS). Four motor imagery tasks (right hand, left hand, right foot, and left foot tapping) were executed while motor cortex activity was recorded via fNIRS. Preliminary results from three participants suggest that this could be a viable BCI interface, with two subjects achieving 50% accuracy. fNIRS is a noninvasive, safe, portable, and affordable optical brain imaging technique used to monitor cortical hemodynamic changes. Because of its portability and ease of use, fNIRS is amenable to deployment in more natural settings. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) BCIs have already been used with up to four motor-imagery-based commands. While fNIRS-based BCIs are relatively new, success with EEG and fMRI systems, as well as signal characteristics similar to fMRI and complementary to EEG, suggest that fNIRS could serve to build or augment future BCIs.

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26 citations in Scopus

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Web of Science research areas
Engineering, Biomedical
Engineering, Electrical & Electronic
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