Feature extraction of P300 signal using Bayesian delay time estimation

Brain-computer interfaces (BCIs) based on event-related potentials (ERP) are communicating tools with severely disabled people. P300 which is observed after 300 mili seconds from stimuli is widely used for the operation principle of BCIs. However the response time to the stimuli depends on a subject, trial, and also a channel. Many existing approaches ignore this variation and extract only low frequency component. We propose a method to estimate the response time of P300 using Bayesian estimation. The proposed method exhibited higher performance in our auditory BCI.