论文标题
脑部计算机界面：研究从视觉诱发到纯粹想象的稳态电位的过渡
Brain-Computer Interfaces: Investigating the Transition from Visually Evoked to Purely Imagined Steady-State Potentials
论文作者
论文摘要
基于稳态视觉诱发电位（SSVEP）的脑部计算机界面（BCI）已被证明有效，并提供了明显的准确性和信息转移率。但是，这种策略家族需要外部设备，以提供该技术所需的频率刺激。这限制了它们可以应用的情况，尤其是与其他BCI方法相比。在这项工作中，我们研究了基于SSVEP弹性刺激的纯粹视觉想象获得EEG输出中频率响应的可能性。我们的结果表明，不仅EEG信号与用户关注的频率相关的当前频率特异性峰，而且还可以达到有希望的分类精度，从而为强大而可靠的可靠视觉图像BCI模式铺平了道路。
Brain-Computer Interfaces (BCIs) based on Steady State Visually Evoked Potentials (SSVEPs) have proven effective and provide significant accuracy and information-transfer rates. This family of strategies, however, requires external devices that provide the frequency stimuli required by the technique. This limits the scenarios in which they can be applied, especially when compared to other BCI approaches. In this work, we have investigated the possibility of obtaining frequency responses in the EEG output based on the pure visual imagination of SSVEP-eliciting stimuli. Our results show that not only that EEG signals present frequency-specific peaks related to the frequency the user is focusing on, but also that promising classification accuracy can be achieved, paving the way for a robust and reliable visual imagery BCI modality.
