Chen Xiaogang, Wang Yijun, Zhang Shangen, Gao Shangkai, Hu Yong, Gao Xiaorong
Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300192, People's Republic of China. Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, People's Republic of China.
J Neural Eng. 2017 Apr;14(2):026013. doi: 10.1088/1741-2552/aa5989. Epub 2017 Jan 16.
Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has been widely investigated because of its easy system configuration, high information transfer rate (ITR) and little user training. However, due to the limitations of brain responses and the refresh rate of a monitor, the available stimulation frequencies for practical BCI application are generally restricted.
This study introduced a novel stimulation method using intermodulation frequencies for SSVEP-BCIs that had targets flickering at the same frequency but with different additional modulation frequencies. The additional modulation frequencies were generated on the basis of choosing desired flickering frequencies. The conventional frame-based 'on/off' stimulation method was used to realize the desired flickering frequencies. All visual stimulation was present on a conventional LCD screen. A 9-target SSVEP-BCI based on intermodulation frequencies was implemented for performance evaluation. To optimize the stimulation design, three approaches (C: chromatic; L: luminance; CL: chromatic and luminance) were evaluated by online testing and offline analysis.
SSVEP-BCIs with different paradigms (C, L, and CL) enabled us not only to encode more targets, but also to reliably evoke intermodulation frequencies. The online accuracies for the three paradigms were 91.67% (C), 93.98% (L), and 96.41% (CL). The CL condition achieved the highest classification performance.
These results demonstrated the efficacy of three approaches (C, L, and CL) for eliciting intermodulation frequencies for multi-class SSVEP-BCIs. The combination of chromatic and luminance characteristics of the visual stimuli is the most efficient way for the intermodulation frequency coding method.
基于稳态视觉诱发电位（SSVEP）的脑机接口（BCI）因其系统配置简单、信息传输率高且用户训练少而受到广泛研究。然而，由于大脑反应和显示器刷新率的限制，实际BCI应用中可用的刺激频率通常受到限制。
本研究介绍了一种用于SSVEP-BCI的新型刺激方法，该方法使用互调频率，使目标以相同频率闪烁但具有不同的附加调制频率。附加调制频率是在选择所需闪烁频率的基础上生成的。采用传统的基于帧的“开/关”刺激方法来实现所需的闪烁频率。所有视觉刺激都呈现在传统的液晶显示屏上。实现了一个基于互调频率的9目标SSVEP-BCI用于性能评估。为了优化刺激设计，通过在线测试和离线分析评估了三种方法（C：色度；L：亮度；CL：色度和亮度）。
具有不同范式（C、L和CL）的SSVEP-BCI不仅使我们能够编码更多目标，而且能够可靠地诱发互调频率。三种范式的在线准确率分别为91.67%（C）、93.98%（L）和96.41%（CL）。CL条件下实现了最高的分类性能。
这些结果证明了三种方法（C、L和CL）在多类SSVEP-BCI中诱发互调频率的有效性。视觉刺激的色度和亮度特征的组合是互调频率编码方法最有效的方式。
