Performance Analysis of a Persian text input brain- computer interface (BCI) P300 speller system with row/column paradigm (RCP)

BCI P300 speller as a Brain computer interface system try to help disabled people and patients to regain some of their lost ability and help them to communicate via typing. The ability of personalization is one of the most important feature in BCI system. The typing language as a personalization factor is one of the most important feature in BCI systems. Most prior research on p300 spellers has focused on displaying English alphabet.in this research, we present a P300 Speller system, based on row or column paradigm, for Persian (Farsi) character input.as performance determination we calculated accuracy and bit rate for the said system based on recorded data from volunteers and reached the average accuracy of 91.39 % and bit rate of 7.22 (bits/minute) (we uses Linear LDA classifier for classification and the total trial number was set to 15). Furthermore in this research performance was measured for different trial number and final results demonstrated that this system can achieve high average accuracy of 82.82 % and average bit rate of 21.52 (bits/minute) by using only 4 repetitions.