Incorporating EEG and fNIRS Patterns to Evaluate Cortical Excitability and MI-BCI Performance During Motor Training

Incorporating EEG and fNIRS Patterns to Evaluate Cortical Excitability and MI-BCI Performance During Motor Training

As electroencephalography (EEG) is nonlinear and nonstationary in nature, an imperative challenge for brain-computer interfaces (BCIs) is to construct a robust classifier that can survive for a long time and monitor the brain state stably. To this end, this research aims to improve BCI performance b...

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Bibliographic Details
Main Authors: Zhongpeng Wang, Lu Yang, Yijie Zhou, Long Chen, Bin Gu, Shuang Liu, Minpeng Xu, Feng He, Dong Ming
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Brain > computer interface
neurofeedback training
hybrid brain signal
weighted EEG-fNIRS patterns
motor imagery
Online Access:https://ieeexplore.ieee.org/document/10141658/

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