Objective . The steady-state visual evoked potential (SSVEP)-based brain computer interface (BCI) has demonstrated relatively high performance with little user training, and thus becomes a popular BCI paradigm. However, due to the performance deterioration over time, its robustness and reliability appear not sufficient to allow a non-expert to use outside laboratory. It would be thus helpful to study what happens behind the decreasing tendency of the BCI performance. Approach. This paper explores the changes of brain networks and electrooculography (EOG) signals to investigate the cognitive capability changes along the use of the SSVEP-based BCI. The EOG signals are characterized by the blink amplitudes and the speeds of saccades, and the brain networks are estimated by the instantaneous phase synchronizations of electroencephalography signals. Main results. Experimental results revealed that the characteristics derived from EOG and brain networks have simil...

中文翻译：

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脑电相位同步和EOG信号的变化，通过使用稳态视觉诱发电位的基于脑的计算机接口。

目标。基于稳态视觉诱发电位（SSVEP）的脑计算机接口（BCI）已显示出相对较高的性能，而用户培训很少，因此成为一种流行的BCI范例。但是，由于性能随时间而下降，它的健壮性和可靠性似乎不足以允许非专家在实验室外使用。因此，研究BCI性能下降趋势背后发生的情况将是有帮助的。方法。本文探讨了脑网络和眼电图（EOG）信号的变化，以研究基于基于SSVEP的BCI的认知能力变化。EOG信号的特征在于眨眼幅度和扫视速度，而脑电图则通过脑电图信号的瞬时相位同步来估计。主要结果。实验结果表明，从EOG和脑网络获得的特征具有相似的...