Personal Identification Number Application Using Adaptive P300 Brain-Computer Interface

Abstract

Here we report the development of a personal identification number (PIN) application using a P300-based brain-computer interface (BCI). We focused on visual stimulation design for increasing the evoked potential in the brain. Single-channel electroencephalography and a computationally inexpensive algorithm were used for P300 detection. Experimental results showed that our proposed stimulus induced higher P300 amplitude than did a conventional stimulus. For a performance evaluation, we compared two versions of the proposed application, which were based on our ‘original P300 BCI’ and ‘adaptive P300 BCI’. In the adaptive P300 BCI, we introduced a novel algorithm for P300 detection to improve the information transfer rate while maintaining acceptable accuracy. Experiments with 10 healthy participants revealed that the original P300 BCI achieved mean accuracy of 83.50% at 11.40 bits/min and the adaptive version achieved mean accuracy of 86.00% at 18.63 bits/min.