Abstract
P300 speller is a communication tool based on Brain Computer Interfaces (BCIs) which allow users to input letters only by thoughts. It uses P300, one of the event-related potential (ERP), as the target feature. In P300 speller, another person starts and closes the system. It is not convenient for a motor impaired user to need other's help at every occasion of switching. To solve this problem, an asynchronous P300 speller which can control ON/OFF automatically based on the user's intention of input is needed. In recent years, the intention classification method with additional pre-training has been proposed. In the additional pre-training, the classifier trains non-control state data which are recorded when the user does not have intension to input letters. However, in order to improve the performance of intention classification, the additional signal recording in several non-control states is needed, which could be burdens for the user. In this paper, we propose and study an intention classification method using only training data in which a user input letters and an asynchronous system in P300 speller based on the user's intention of input.
