A Survey on EEG-fNIRS based Non-invasive hBCIs

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.