How to encode as many targets as possible with a limited-frequency resource is a difficult problem in the practical use of a steady-state visual evoked potential (SSVEP) based brain-computer interface (BCI) speller. To solve this problem, this study developed a novel method called dual-frequency biased coding (DFBC) to tag targets in a SSVEP-based 48-character virtual speller, in which each target is encoded with a permutation sequence consisting of two permuted flickering periods that flash at different frequencies. The proposed paradigm was validated by 11 participants in an offline experiment and 7 participants in an online experiment. Three occipital channels (O1, Oz, and O2) were used to obtain the SSVEP signals for identifying the targets. Based on the coding characteristics of the DFBC method, the proposed approach has the ability of self-correction and thus achieves an accuracy of 76.6% and 79.3% for offline and online experiments, respectively, which outperforms the traditional multiple frequencies sequential coding (MFSC) method. This study demonstrates that DFBC is an efficient method for coding a high number of SSVEP targets with a small number of available frequencies.

中文翻译：

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基于SSVEP的基于双频偏置编码的有限频率脑机接口


如何利用有限的频率资源对尽可能多的目标进行编码是基于稳态视觉诱发电位（SSVEP）的脑机接口（BCI）拼写器实际使用中的一个难题。为了解决这个问题，本研究开发了一种称为双频偏向编码 (DFBC) 的新颖方法，用于在基于 SSVEP 的 48 字符虚拟拼写器中标记目标，其中每个目标都使用由两个排列闪烁周期组成的排列序列进行编码以不同的频率闪烁。所提出的范式由 11 名离线实验参与者和 7 名在线实验参与者验证。使用三个枕骨通道（O1、Oz 和 O2）来获取 SSVEP 信号以识别目标。基于DFBC方法的编码特点，该方法具有自纠错能力，离线和在线实验的准确率分别达到76.6%和79.3%，优于传统的多频顺序编码（MFSC）方法。这项研究表明，DFBC 是一种用少量可用频率编码大量 SSVEP 目标的有效方法。