Benda Mihaly, Volosyak Ivan
Faculty of Technology and Bionics, Rhine-Waal University of Applied Sciences, 47533 Kleve, Germany.
Brain Sci. 2020 Apr 18;10(4):240. doi: 10.3390/brainsci10040240.
In this paper we compared different visual feedback methods, informing users about classification progress in a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) speller application. According to results from our previous studies, changes in stimulus size and contrast as online feedback of classification progress have great impact on BCI performance in SSVEP-based spellers. In this experiment we further investigated these effects, and tested a 4-target SSVEP speller interface with a much higher number of subjects. Five different scenarios were used with variations in stimulus size and contrast, "", "", "", "", and "". With each of the five scenarios, 24 participants had to spell six letter words (at least 18 selections with this three-steps speller). The fastest feedback modalities were different for the users, there was no visual feedback which was generally better than the others. With the used interface, six users achieved significantly better Information Transfer Rates (ITRs) compared to the "" condition. Their average improvement by using the individually fastest feedback method was 46.52%. This finding is very important for BCI experiments, as by determining the optimal feedback for the user, the speed of the BCI can be improved without impairing the accuracy.
在本文中，我们比较了不同的视觉反馈方法，这些方法用于在基于稳态视觉诱发电位（SSVEP）的脑机接口（BCI）拼写器应用中告知用户分类进度。根据我们之前研究的结果，作为分类进度的在线反馈，刺激大小和对比度的变化对基于SSVEP的拼写器中的BCI性能有很大影响。在本实验中，我们进一步研究了这些影响，并在更多受试者上测试了一个4目标的SSVEP拼写器界面。使用了五种不同的场景，刺激大小和对比度有所变化，分别为“”、“”、“”、“”和“”。对于这五种场景中的每一种，24名参与者都必须拼写六个字母的单词（使用这个三步拼写器至少进行18次选择）。对用户来说，最快的反馈方式各不相同，没有一种视觉反馈普遍优于其他反馈。使用该界面时，与“”条件相比，有六名用户实现了显著更高的信息传输率（ITR）。通过使用各自最快的反馈方法，他们的平均提升幅度为46.52%。这一发现对BCI实验非常重要，因为通过为用户确定最佳反馈，可以在不损害准确性的情况下提高BCI的速度。
