Abstract
The P300 brain–computer interface (BCI) system relies on an oddball paradigm to elicit the P300. Besides the traditional row/column paradigm (RCP), many visual paradigms have been proposed for the P300 BCI. In our previous work, submatrix-based paradigm (SBP) was proposed and proven to be superior to the RCP in performance and user acceptability. To further improve the performance and realize an online BCI system, a dynamic SBP online BCI is proposed in this paper. The dynamic algorithm employs a threshold which dynamically limits the number of sequences. Based on analyzing the distribution characteristic of P300 in SBP, two threshold algorithms named the maximum value algorithm and the pseudo-kurtosis algorithm are proposed and compared. Online experimental results show that both dynamic algorithms can improve the performance of the SBP P300 speller, and the mean practical bit rate of the maximum value algorithm is 34.36bits/min, which is 9.04% higher than that of checkerboard paradigm (CBP) and 11.2% higher than that of Jin's n-flash adaptive system (NFA).
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