Most research in Brain-Computer-Interfaces (BCI) focuses on technologies to improve accuracy and speed. Little has been done on the effects of subject variability, both across individuals and within the same individual, on BCI performance. For example, stress, arousal, motivation, and fatigue can all affect the electroencephalogram (EEG) signals used by a BCI, which in turn impacts performance. Overcoming the impact of such user variability on BCI performance is an impending and inevitable challenge for routine applications of BCIs in the real world. To systematically explore the factors affecting BCI performance, this study embeds a Steady-State Visually Evoked Potential (SSVEP) based BCI into a “game with a purpose” (GWAP) to obtain data over significant lengths of time, under both high- and low-stress conditions. Ten healthy volunteers played a GWAP that resembles popular match-three games, such as Jewel Quest, Zoo Boom, or Candy Crush. We recorded the target search time, target search accuracy, and EEG signals during gameplay to investigate the impacts of stress on EEG signals and BCI performance. We used Canonical Correlation Analysis (CCA) to determine whether the subject had found and attended to the correct target. The experimental results show that SSVEP target-classification accuracy is reduced by stress. We also found a negative correlation between EEG spectra and the SNR of EEG in the frontal and occipital regions during gameplay, with a larger negative correlation for the high-stress conditions. Furthermore, CCA also showed that when the EEG alpha and theta power increased, the search accuracy decreased, and the spectral amplitude drop was more evident under the high-stress situation. These results provide new, valuable insights into research on how to improve the robustness of BCIs in real-world applications.

中文翻译：

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静息脑电图谱中的压力诱导效应可预测基于 SSVEP 的 BCI 的性能


大多数脑机接口（BCI）研究都集中在提高准确性和速度的技术上。关于受试者变异性（无论是个体间还是同一个体内）对 BCI 表现的影响，人们几乎没有做过任何研究。例如，压力、觉醒、动机和疲劳都会影响 BCI 使用的脑电图 (EEG) 信号，进而影响性能。克服这种用户变化对 BCI 性能的影响是 BCI 在现实世界中的常规应用迫在眉睫且不可避免的挑战。为了系统地探索影响 BCI 性能的因素，本研究将基于稳态视觉诱发电位 (SSVEP) 的 BCI 嵌入到“有目的的游戏”(GWAP) 中，以在高和低条件下获取相当长的时间段内的数据。 -压力条件。十名健康的志愿者玩了类似于流行的三消游戏的 GWAP，例如《宝石探秘》、《动物园繁荣》或《糖果粉碎传奇》。我们记录了游戏过程中的目标搜索时间、目标搜索准确性和脑电图信号，以研究压力对脑电图信号和脑机接口性能的影响。我们使用典型相关分析（CCA）来确定受试者是否找到并关注了正确的目标。实验结果表明，SSVEP 目标分类精度会因压力而降低。我们还发现，在游戏过程中，脑电图谱与额叶和枕叶区脑电图信噪比之间存在负相关性，并且在高压力条件下负相关性更大。此外，CCA还表明，当EEG alpha和theta功率增加时，搜索精度下降，并且在高压力情况下频谱幅度下降更加明显。 这些结果为如何提高 BCI 在实际应用中的稳健性的研究提供了新的、有价值的见解。