Significant Neurophysiological Features for fNIRS-EEG Brain-Computer Interfacing of Imagined Speech

Abstract

Brain-computer interface (BCI) is a computer-based technology that allows the human brain to communicate with external devices. Imagined speech is a mental task that has recently garnered attention as an intuitive BCI task; however, it can be difficult to identify and classify. As a result, this study aims to investigate the significant neurophysiological response based on EEG and fNIRS signals of imagined speech. Seven participants performed yes-no imagined speech. The neurophysiological response features were extracted using a combination of brain regions (spatial resolution), response characteristics, and time windows. The Friedman test, a statistical analysis method, was used to determine whether any significant differences in any neurophysiological response feature on an imagined speech word across subjects. The most significant region in both EEG and fNIRS was the frontal and parietal regions. These findings and other significant neurophysiological response features can be utilized to improve the BCI system.