Identification of gait imagery based on fNIRS and class-dependent sparse representation

Optical imaging and spectroscopy for the study of the human brain: status report

“…449 This approach to active rehabilitation aims to replace the disrupted neuromuscular pathways of humans caused by disorders or amputation with wearable robotic devices. 450 The recent advances in fNIRS-based BCI studies focus on their applications for (i) the movement control of robots and exoskeletons, (ii) detecting and preventing brain disorders, (iii) analyzing and controlling psychophysiological states, and (iv) monitoring and controlling pathological and normal cognitive activity. 451 Despite an exponential increase in fNIRS-based BCI-related publications and financial investment efforts during the last two decades, the clinical success of fNIRS-based BCI applications is still pending.…”

Applying antagonistic activation pattern to the single-trial classification of mental arithmetic

“…The technique that uses electrophysiological signals is electroencephalography (EEG), which records the electrical signals generated by the neuronal activity of the brain [ 9 , 10 ]. Non-invasive BCI for recording hemodynamic responses uses functional neuroimaging techniques, for example, functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) [ 11 , 12 , 13 , 14 ]. fMRI and fNIRS capture the changes in oxygen concentration in the blood consumed by neuronal activity in the brain and indirectly record neuronal activity.…”