TY - JOUR
T1 - Multi-modal integration of EEG-fNIRS for brain-computer interfaces – Current limitations and future directions
AU - Ahn, Sangtae
AU - Jun, Sung C.
N1 - Publisher Copyright:
© 2017 Ahn and Jun.
PY - 2017/10/18
Y1 - 2017/10/18
N2 - 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 costeffective 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.
AB - 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 costeffective 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.
KW - Brain-computer interface (BCI)
KW - Electroencephalography (EEG)
KW - Functional near-infrared spectroscopy (fNIRS)
KW - Multi-modal integration
UR - http://www.scopus.com/inward/record.url?scp=85031995382&partnerID=8YFLogxK
U2 - 10.3389/fnhum.2017.00503
DO - 10.3389/fnhum.2017.00503
M3 - Review article
AN - SCOPUS:85031995382
SN - 1662-5161
VL - 11
JO - Frontiers in Human Neuroscience
JF - Frontiers in Human Neuroscience
M1 - 503
ER -