Incremental learning to reduce the burden of machine learning for P300 speller

The P300 speller is one of the BCI applications, which allows users to select letters just by thoughts. However, due to the difference of P300 in each person and with the passage of time, users are required to do machine learning every time before use (pre-training). This pre-training is a burden to users. This paper proposes an incremental learning using unknown data to reduce the training time. Consequently, this paper shows that the proposed method gives not only the reduction of the training time but also directly use of P300 speller without pre-training by using the data of last time.