TY - GEN
T1 - A Survey on EEG-fNIRS based Non-invasive hBCIs
AU - Sial, Muhammad Baber
AU - Wang, Shaoping
AU - Wang, Xingjian
AU - Wyrwa, Justyna
AU - Ali, Sara
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/5
Y1 - 2021/4/5
N2 - Brain-computer Interface (BCI) is a communications structure in which signals acquired from brain are used to control paralyzed human limbs, computers and various kinds of devices. BCI systems are trying to restore a certain degree of independence to severely disabled people with a hope to improve their quality of life. In this paper, we attempt to conceptualize several methods regarding EEG-fNIRS hybrid BCIs (hBCI) founded on recent literature. By analyzing specific techniques such as detecting changes in hemodynamic response signals by slope indicators in fNIRS BCIs, using modified vector phase analysis to improve classification accuracy of EEG-fNIRS and increasing the number of commands by collecting EEG-fNIRS signals from different regions of the brain, superiority of these systems for future use is established with an underlying precondition that some key limitations pertaining to these techniques be resolved in time.
AB - Brain-computer Interface (BCI) is a communications structure in which signals acquired from brain are used to control paralyzed human limbs, computers and various kinds of devices. BCI systems are trying to restore a certain degree of independence to severely disabled people with a hope to improve their quality of life. In this paper, we attempt to conceptualize several methods regarding EEG-fNIRS hybrid BCIs (hBCI) founded on recent literature. By analyzing specific techniques such as detecting changes in hemodynamic response signals by slope indicators in fNIRS BCIs, using modified vector phase analysis to improve classification accuracy of EEG-fNIRS and increasing the number of commands by collecting EEG-fNIRS signals from different regions of the brain, superiority of these systems for future use is established with an underlying precondition that some key limitations pertaining to these techniques be resolved in time.
KW - Brain Computer Interfaces (BCI)
KW - electroencephalography (EEG)
KW - functional near-infrared spectroscopy (fNIRS)
KW - Hybrid Brain Computer Interfaces hBCI
UR - https://www.scopus.com/pages/publications/85108117154
U2 - 10.1109/ICAI52203.2021.9445246
DO - 10.1109/ICAI52203.2021.9445246
M3 - 会议稿件
AN - SCOPUS:85108117154
T3 - 2021 International Conference on Artificial Intelligence, ICAI 2021
SP - 240
EP - 245
BT - 2021 International Conference on Artificial Intelligence, ICAI 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 International Conference on Artificial Intelligence, ICAI 2021
Y2 - 5 April 2021 through 7 April 2021
ER -