Multi-Modal Integration of EEG-fNIRS for Brain-Computer Interfaces - Current Limitations and Future Directions

Ahn S, Jun SC

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Abstract

Multi-modal integration, which combines multiple neurophysiological signals, is gaining more attention for its potential to supplement single modality's drawbacks and yield reliable results by extracting complementary features. In particular, integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) is cost-effective and portable, and therefore is a fascinating approach to brain-computer interface (BCI). However, outcomes from the integration of these two modalities have yielded only modest improvement in BCI performance because of the lack of approaches to integrate the two different features. In addition, mismatch of recording locations may hinder further improvement. In this literature review, we surveyed studies of the integration of EEG/fNIRS in BCI thoroughly and discussed its current limitations. We also suggested future directions for efficient and successful multi-modal integration of EEG/fNIRS in BCI systems.

Abstract of "Multi-Modal Integration of EEG-fNIRS for Brain-Computer Interfaces - Current Limitations and Future Directions" by Ahn S, Jun SC, https://doi.org/10.3389/fnhum.2017.00503, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.

Record

Archive ID
doi:10.3389/fnhum.2017.00503
Published
Oct 18, 2017
Venue
Frontiers in human neuroscience
DOI
10.3389/fnhum.2017.00503
PubMed
29093673
PMC
PMC5651279
License
CC-BY
Provenance
europepmc

Topics