基于P300和视觉失配消极性的优化BCI系统

2015 2nd International Conference on Information Science and Control Engineering Pub Date : 2015-04-24 DOI:10.1109/ICISCE.2015.143

Sijie Zhou, Jing Jin, Yu Zhang, Xingyu Wang

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引用次数: 0

摘要

本文提出了一种脑机接口(BCI)，在该接口中，人脸范式针对视觉错配否定(MMN)进行了优化。液晶显示器上有12个单元格。每个格子的底部都有一个字母。在新的范例中，12个单元格上随机出现一张彩色面孔，而灰色面孔出现在另外11个单元格上。比较了单一字符模式的传统人脸范式。3名健康受试者参加了实验。结果表明，新范式在网络会话中诱导的N200和N400成分比传统面孔范式大，且具有更好的表现。结果表明了P300拼字系统中新范式的优越性。

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An Optimized BCI System Based on P300 and Visual Mismatch Negativity

This paper presents a brain-computer interface (BCI) in which the face paradigm was optimized for the visual mismatch negativity (MMN). There were 12 cells in a LCD monitor. A single letter was at the bottom of each cell. In the new paradigm, a color face appeared above each of the 12 cells randomly while the gray faces appeared in others 11 cells. A traditional face paradigm with single character pattern was compared. Three healthy subjects participated in the experiment. Results showed that the new paradigm elicited larger N200 and N400 components than traditional face paradigm and had better performance in online session. The results demonstrated the advantages of the new paradigm in our P300 speller system.

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2015 2nd International Conference on Information Science and Control Engineering

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