Analysis of Hypertension using Fusion of EEG and fNIRS Features

Brain-computer interface (BCI) or brain–machine interface (BMI) is a way to communicate between the brain and hardware without the use of muscles or the peripheral nervous system. Simultaneous EEG+fNIRS metric have recently been developed. Until now, few researchers have analysed the possibilities of incorporating hemodynamic responses to their electrophysiologic counterparts in a hybrid way to increase overall performance of the system and accuracy. The combination of fNIRS and EEG signals provide a hybrid sensory motor rhythm based on a brain computer interface (BCI) paradigm. A meta-classifier has been designed to integrate the output probability of each classifier modality. The study found that the simultaneous EEG+fNIRS measurement can substantially improve classification precision.