A novel exactly periodic spatial filtering (EPSD) approach, that provides a robust detection performance, is introduced and evaluated in this study. The proposed method exploits the temporal properties of the steady-state visual evoked potential (SSVEP) response to construct an orthogonal and exactly periodic mapping that enhances the signal to noise ratio (SNR) of the SSVEP embedded in the electroencephalogram (EEG) data. The subspace of interest is constructed via the elimination of the signals spaces that does not constitute the exact period of the target frequency. The EPSD is evaluated on a 35 subject benchmark dataset collected using a 40 target SSVEP BCI system. The results reveal that the proposed EPSD spatial filter significantly enhances the performance of target detection. Further statistical tests also confirm that the EPSD is a potential alternative to the existing SSVEP spatial filters for realizing an efficient BCI system.

本研究介绍并评估了一种新颖的精确周期性空间滤波（EPSD）方法，该方法可提供强大的检测性能。所提出的方法利用稳态视觉诱发电位（SSVEP）响应的时间特性来构建正交且精确的周期性映射，以增强嵌入在脑电图（EEG）数据中的SSVEP的信噪比（SNR）。感兴趣的子空间是通过消除不构成目标频率确切周期的信号空间来构造的。在使用40个目标SSVEP BCI系统收集的35个主题基准数据集上评估EPSD。结果表明，提出的EPSD空间滤波器显着提高了目标检测的性能。