Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:222-225. doi: 10.1109/EMBC48229.2022.9870831.
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. Clinical relevance-Brain computer interfaces play a fundamental role in enhancing the quality of life of patients with severe motor impairments. Strategies based on purely imagined stimuli, like the one presented here, are particularly impacting, especially in the most severe cases.
基于稳态视觉诱发电位（SSVEP）的脑-机接口（BCI）已被证明是有效的，并提供了较高的准确性和信息传输率。然而，这类策略需要外部设备来提供该技术所需的频率刺激，这限制了它们的应用场景，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 诱发刺激的纯视觉想象获得脑电输出中频率响应的可能性。我们的结果表明，不仅 EEG 信号呈现出与用户关注频率相关的特定频率的峰值，而且还可以实现有前景的分类准确性，为一种稳健可靠的视觉想象 BCI 模式铺平了道路。临床相关性-脑机接口在提高严重运动障碍患者的生活质量方面发挥着重要作用。像这里提出的这种基于纯想象刺激的策略尤其具有影响力，特别是在最严重的情况下。
