Developments in Hybrid Brain-Computer Interfaces: Foundations, Architecture, and Uses

Abstract

Two major issues have plagued traditional brain-computer interface (BCI) systems: the control
command issue and the low detection performance. In order to overcome these obstacles, the researchers have
suggested a hybrid brain-computer interface (hBCI). This study analyzes three forms of hBCI: multisensory
hBCI, hBCI based on multimodal signals, and hBCI based on multiple brain models. It also primarily discusses
the research progress of hBCI. By examining the general concepts, paradigm designs, experimental findings,
benefits, and uses of the most recent hBCI system, we discovered that utilizing hBCI technology can enhance
BCI detection performance and accomplish multidegree/multifunctional control, which is noticeably better than
single-mode BCIs.