Zhang Xinru, Jin Jing, Li Shurui, Wang Xingyu, Cichocki Andrzej
Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, People's Republic of China.
Skolkovo Institute of Science and Technology (Skoltech), 121205 Moscow, Russia.
Cogn Neurodyn. 2021 Oct;15(5):873-886. doi: 10.1007/s11571-021-09669-y. Epub 2021 Feb 21.
The stimulus color of P300-BCI systems has been successfully modified. However, the effects of different color combinations have not been widely investigated. In this study, we designed new stimulus patterns to evaluate the influence of color modulation on the BCI performance and waveforms of the evoked related potential (ERP). Comparison was performed for three new stimulus patterns consisting of red face and colored block-shape, namely, red face with a white rectangle (RFW), red face with a blue rectangle (RFB), and red face with a red rectangle (RFR). Bayesian linear discriminant analysis (BLDA) was used to construct the individual classifier model. Repeated-measures ANOVA and Bonferroni correction were applied for statistical analysis. The RFW pattern obtained the highest average online accuracy with 96.94%, and those of RFR and RFB patterns were 93.61% and of 92.22% respectively. Significant differences in online accuracy and information transfer rate (ITR) were found between RFW and RFR patterns ( < 0.05). Compared with RFR and RFB patterns, RFW yielded the best performance in P300-BCI. These new stimulus patterns with different color combinations have considerable importance to BCI applications and user-friendliness.
P300脑机接口系统的刺激颜色已成功改变。然而，不同颜色组合的影响尚未得到广泛研究。在本研究中，我们设计了新的刺激模式，以评估颜色调制对脑机接口性能和诱发相关电位（ERP）波形的影响。对由红脸和彩色块状组成的三种新刺激模式进行了比较，即红脸加白色矩形（RFW）、红脸加蓝色矩形（RFB）和红脸加红色矩形（RFR）。采用贝叶斯线性判别分析（BLDA）构建个体分类器模型。应用重复测量方差分析和Bonferroni校正进行统计分析。RFW模式获得了最高的平均在线准确率，为96.94%，RFR和RFB模式的准确率分别为93.61%和92.22%。RFW和RFR模式在在线准确率和信息传输率（ITR）方面存在显著差异（<0.05）。与RFR和RFB模式相比，RFW在P300脑机接口中表现最佳。这些具有不同颜色组合的新刺激模式对脑机接口应用和用户友好性具有重要意义。
