EEG signal pre-processing for the P300 speller

Abstract

One of the workhorses of Brain Computer Interfaces (BCI) is the P300 speller, which allows a person to spell text by looking at the corresponding letters that are laid out on a flashing grid. The device functions by detecting the Event Related Potentials (ERP), which can be measured in an electroencephalogram (EEG), that occur when the letter that the subject is looking at flashes (unexpectedly). In this work, after a careful analysis of the EEG signals involved, we propose a preprocessing method that allows us to improve on the state-of-the-art results for this kind of applications. Our results are comparable, and sometimes better, than the best results published, and do not require a feature (channel) selection step, which is extremely costly, and which must be adapted to each user of the P300 speller separately.