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A visual parallel-BCI speller based on the time-frequency coding strategy
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DOI：10.1088/1741-2560/11/2/026014.png)
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Abstract
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Objective. Spelling is one of the most important issues in brain computer interface (BCI) research. This paper is to develop a visual parallel-BCI speller system based on the time frequency coding strategy in which the sub-speller switching among four simultaneously presented sub-spellers and the character selection are identified in a parallel mode. Approach. The parallel-BCI speller was constituted by four independent P300+SSVEP-B (P300 plus SSVEP blocking) spellers with different flicker frequencies, thereby all characters had a specific time frequency code. To verify its effectiveness, 11 subjects were involved in the offline and online spellings. A classification strategy was designed to recognize the target character through jointly using the canonical correlation analysis and stepwise linear discriminant analysis. Main results. Online spellings showed that the proposed parallel-BCI speller had a high performance, reaching the highest information transfer rate of 67.4 bit min(-1), with an average of 54.0 bit min(-1) and 43.0 bit min(-1) in the three rounds and five rounds, respectively. Significance. The results indicated that the proposed parallel-BCI could be effectively controlled by users with attention shifting fluently among the sub-spellers, and highly improved the BCI spelling performance.
Keywords:
brain-computer interface
hybrid paradigm
parallel system
ERP
SSVEP
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