EEG character identification using stimulus sequences designed to maximize mimimal hamming distance

In this study, we have improved upon the P300 speller Brain-Computer Interface paradigm by introducing a new character encoding method. Our concept in detection of the intended character is not based on a classification of target and nontarget responses, but based on an identification of the character which maximize the difference between P300 amplitudes in target and nontarget stimuli. Each bit included in the code corresponds to flashing character, `1´, and non-flashing, `0´. Here, the codes were constructed in order to maximize the minimum hamming distance between the characters. Electroencephalography was used to identify the characters using a waveform calculated by adding and subtracting the response of the target and non-target stimulus according the codes respectively. This stimulus presentation method was applied to a 3×3 character matrix, and the results were compared with that of a conventional P300 speller of the same size. Our method reduced the time until the correct character was obtained by 24%.