Sangin Park

Deep learning-based speller system for decoding user intentions from pupillary light reflex signals using time-division flickering visual stimuli

Despite extensive studies on brain–computer interface (BCI)-based speller systems for individuals with motor disabilities as communication aids and, more recently, for healthy users as hands-free input devices, these systems continue to face practical limitations, including calibration and training requirements, high...