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一种基于失配负波范式修正的 P300 脑-机接口。

A P300 brain-computer interface based on a modification of the mismatch negativity paradigm.

机构信息

Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China.

出版信息

Int J Neural Syst. 2015 May;25(3):1550011. doi: 10.1142/S0129065715500112. Epub 2015 Feb 26.

Abstract

The P300-based brain-computer interface (BCI) is an extension of the oddball paradigm, and can facilitate communication for people with severe neuromuscular disorders. It has been shown that, in addition to the P300, other event-related potential (ERP) components have been shown to contribute to successful operation of the P300 BCI. Incorporating these components into the classification algorithm can improve the classification accuracy and information transfer rate (ITR). In this paper, a single character presentation paradigm was compared to a presentation paradigm that is based on the visual mismatch negativity. The mismatch negativity paradigm showed significantly higher classification accuracy and ITRs than a single character presentation paradigm. In addition, the mismatch paradigm elicited larger N200 and N400 components than the single character paradigm. The components elicited by the presentation method were consistent with what would be expected from a mismatch paradigm and a typical P300 was also observed. The results show that increasing the signal-to-noise ratio by increasing the amplitude of ERP components can significantly improve BCI speed and accuracy. The mismatch presentation paradigm may be considered a viable option to the traditional P300 BCI paradigm.

摘要

基于 P300 的脑机接口(BCI)是一种扩展的奇异范式,可以促进严重神经肌肉障碍患者的交流。已经表明,除了 P300 之外,其他事件相关电位(ERP)成分也被证明有助于成功运行 P300 BCI。将这些成分纳入分类算法可以提高分类准确性和信息传输率(ITR)。在本文中,将单个字符呈现范式与基于视觉失匹配负波的呈现范式进行了比较。失匹配范式的分类准确性和 ITR 明显高于单个字符呈现范式。此外,失匹配范式诱发的 N200 和 N400 成分比单个字符范式大。呈现方法引起的成分与失匹配范式和典型 P300 预期的成分一致。结果表明,通过增加 ERP 成分的幅度来增加信噪比可以显著提高 BCI 的速度和准确性。失配呈现范式可能被认为是传统 P300 BCI 范式的一种可行选择。

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