Gong Minghong, Xu Guizhi, Li Mengfan, Lin Fang
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, CO 300132 China; Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin, CO 300132 China.
State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, CO 300132 China; Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin, CO 300132 China.
J Neurosci Methods. 2020 May 1;337:108670. doi: 10.1016/j.jneumeth.2020.108670. Epub 2020 Mar 3.
An asynchronous brain-computer interface (BCI) allows subject to freely switch between the working state and the idle state, improving the subject's comfort. However, using only the event-related potential (ERP) to detect these two states is difficult because of the small amplitude of the ERP.
Our previous study finds that an odd-ball paradigm could evoke transient visual evoked potentials (TSVEPs) simultaneously with ERPs. This study adopts the TSVEP and the ERP to detect the idle state in the design of an asynchronous TSVEP-ERP-based BCI (T-E BCI). The T-E BCI extracts time and frequency features from brain signals and uses a novel probability-based fisher linear discriminant analysis (P-FLDA) to combine the classification results of the ERP and the TSVEP.
Ten subjects perform visual speller and video watching experiments, and their brain signals are measured under the working and idle states. The main results show that the T-E BCI achieves a higher accuracy than the ERP-based BCI when judging the subject's intentions and the two states. The P-FLDA performs better than the FLDA in combining the classification results.
The study demonstrates that adding the TSVEP can substantially reduce the number of wrongly detected trials. The T-E BCI provides a new way of designing an asynchronous BCI without adding any additional visual stimuli, which makes the BCI more practical.
异步脑机接口（BCI）允许受试者在工作状态和空闲状态之间自由切换，从而提高受试者的舒适度。然而，由于事件相关电位（ERP）的幅度较小，仅使用ERP来检测这两种状态具有一定难度。
我们之前的研究发现，odd-ball范式能够在诱发ERP的同时诱发瞬态视觉诱发电位（TSVEP）。本研究在基于异步TSVEP-ERP的BCI（T-E BCI）设计中采用TSVEP和ERP来检测空闲状态。T-E BCI从脑电信号中提取时间和频率特征，并使用一种新型的基于概率的Fisher线性判别分析（P-FLDA）来融合ERP和TSVEP的分类结果。
10名受试者进行了视觉拼写和视频观看实验，并在工作和空闲状态下测量了他们的脑电信号。主要结果表明，在判断受试者意图和两种状态时，T-E BCI比基于ERP的BCI具有更高的准确率。在融合分类结果方面，P-FLDA比FLDA表现更好。
该研究表明，添加TSVEP可以大幅减少误检测试验的数量。T-E BCI提供了一种无需添加任何额外视觉刺激来设计异步BCI的新方法，这使得BCI更具实用性。
