IEEE Trans Neural Syst Rehabil Eng. 2023;31:3492-3500. doi: 10.1109/TNSRE.2023.3308779. Epub 2023 Sep 4.
Hybrid brain-computer interface (hBCI) systems that combine steady-state visual evoked potential (SSVEP) and surface electromyography (sEMG) signals have attracted attention of researchers due to the advantage of exhibiting significantly improved system performance. However, almost all existing studies adopt low-frequency SSVEP to build hBCI. It produces much more visual fatigue than high-frequency SSVEP. Therefore, the current study attempts to build a hBCI based on high-frequency SSVEP and sEMG. With these two signals, this study designed and realized a 32-target hBCI speller system. Thirty-two targets were separated from the middle into two groups. Each side contained 16 sets of targets with different high-frequency visual stimuli (i.e., 31-34.75 Hz with an interval of 0.25 Hz). sEMG was utilized to choose the group and SSVEP was adopted to identify intra-group targets. The filter bank canonical correlation analysis (FBCCA) and the root mean square value (RMS) methods were used to identify signals. Therefore, the proposed system allowed users to operate it without system calibration. A total of 12 healthy subjects participated in online experiment, with an average accuracy of 93.52 ± 1.66% and the average information transfer rate (ITR) reached 93.50 ± 3.10 bits/min. Furthermore, 12 participants perfectly completed the free-spelling tasks. These results of the experiments indicated feasibility and practicality of the proposed hybrid BCI speller system.
混合脑-机接口（hBCI）系统结合稳态视觉诱发电位（SSVEP）和表面肌电（sEMG）信号，由于表现出显著提高的系统性能的优势，引起了研究人员的关注。然而，几乎所有现有的研究都采用低频 SSVEP 来构建 hBCI。它比高频 SSVEP 产生更多的视觉疲劳。因此，本研究试图构建基于高频 SSVEP 和 sEMG 的 hBCI。通过这两种信号，本研究设计并实现了一个 32 目标的 hBCI 拼写器系统。32 个目标从中间分为两组。每侧包含 16 组具有不同高频视觉刺激的目标（即 31-34.75 Hz，间隔 0.25 Hz）。sEMG 用于选择组，SSVEP 用于识别组内目标。采用滤波器组典型相关分析（FBCCA）和均方根值（RMS）方法识别信号。因此，所提出的系统允许用户在无需系统校准的情况下进行操作。共有 12 名健康受试者参加了在线实验，平均准确率为 93.52±1.66%，平均信息传输率（ITR）达到 93.50±3.10 bits/min。此外，12 名参与者完美地完成了自由拼写任务。这些实验结果表明了所提出的混合 BCI 拼写器系统的可行性和实用性。
