一种新的运动启动N200\P300脑机接口模式*

Tao Xue, Jun Xie, Guanghua Xu, Peng Fang, Guiling Cui, Guanglin Li, Guozhi Cao, Yanjun Zhang, T. Tao, Min Li, Xiaodong Zhang
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引用次数: 0

摘要

事件相关电位(ERP)成分P300和N200被认为是反映认知功能最有价值的电生理指标。传统的罕见事件P300- bci范式通常只将P300组件作为目标特征,而忽略了N200组件。在本文中,我们提出了一种新的运动启动的N200\P300脑机接口(BCI)范式,该范式可以同时引起显著的N200和P300反应。为了评估所提出的新型脑机接口范式的实用性和诱发的N200\P300分量的鲁棒性,采用线性判别分析(LDA)、逐步线性判别分析(SWLDA)和支持向量机(SVM)三种不同算法原理的分类器对识别精度进行了分析。我们还将运动开始的N200\P300数据与无N200部分进行了比较,以评估N200分量对BCI精度提高的影响。实验结果表明,通过该N200\P300组合特征,BCI准确率显著提高,假阳性率显著降低,表明所提出的运动启动型N200\P300 BCI范式具有优于传统P300-BCI范式的性能。
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A Novel Motion-Onset N200\P300 Brain-Computer Interface Paradigm*
The event related potential (ERP) component P300 and N200 are considered to be the most valuable electrophysiological indicators to reflect cognitive function. The traditional rare-event P300-BCI paradigm usually only takes P300 component as the target feature but ignores the N200 component. In this paper, we proposed a novel motion-onset N200\P300 brain-computer interface (BCI) paradigm, which could evoke significant N200 and P300 responses simultaneously. To evaluate the practicality of the proposed novel BCI paradigm and the robustness of the evoked N200\P300 components, three different classifiers of linear discriminant analysis (LDA), stepwise linear discriminant analysis (SWLDA) and support vector machine (SVM) with different algorithm principles were used to analyze the recognition accuracy. We also compared the motion-onset N200\P300 data with an N200-free portion to evaluate the impact of N200 component on the improvement of the BCI accuracy. Experimental results showed that, by means of this N200\P300 combination feature, the BCI accuracy significantly increased and the false positive rate significantly decreased, indicating that the proposed motion-onset N200\P300 BCI paradigm has superior performance than a traditional P300-BCI paradigm.
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