Inter-subject information contributes to the ERP classification in the P300 speller

This study aims to investigate whether the inter-subject information is beneficial to the event-related potential (ERP) classification in the P300-speller. To this end, a classification strategy of weighted ensemble learning generic information (WELGI) was developed, in which the base classifiers constructed by combining both intra- and inter-subject information were integrated into a strong classifier with weight assessments. To verify the algorithm´s validity, 55 subjects were recruited to spell 20 characters offline by using the conventional P300-speller paradigm, and the ERP accuracy and precision were investigated. Compared with the traditional classification strategy only using the intra-subject information, the WELGI could achieve significantly higher ERP accuracy and precision. It was demonstrated that the inter-subject information was beneficial to the ERP classification in the P300-speller.