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A region-based P300 speller for brain-computer interface

机译:基于区域的P300拼写器,用于人机界面

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摘要

A brain-computer interface (BCI) is a system that conveys messages and commands directly from the human brain to a computer. The BCI system described in this work is based on the P300 wave. The P300 is a positive peak of an event-related potential (ERP) that occurs 300 ms after a stimulus. One of the best-known and most widely used P300 applications is the P300 speller designed by Farwell-Donchin in 1988. The Farwell-Donchin paradigm has been a benchmark for P300 BCIs. In this paradigm, a 6 X 6 matrix of letters and numbers is displayed, and the subject focuses on a target character while rows and columns of characters flash. Through detection of P300 for one row and one column, the target character can be identified. In this paper, it is shown that there is a human perceptual error in the Farwell-Donchin paradigm. To eliminate this error, a new region-based paradigm is presented. Using experimental results, it is shown that the new paradigm has several advantages over the Farwell-Donchin paradigm and achieves better accuracy.
机译:脑机接口(BCI)是将信息和命令直接从人脑传递到计算机的系统。在这项工作中描述的BCI系统是基于P300波。 P300是事件相关电位(ERP)的正峰值,发生在刺激后300毫秒。 Farwell-Donchin于1988年设计的P300拼写器是最著名和使用最广泛的P300应用程序之一。Farwell-Donchin范式已成为P300 BCI的基准。在此范例中,显示了一个由字母和数字组成的6 X 6矩阵,并且当字符的行和列闪烁时,对象聚焦于目标字符。通过检测P300的一行和一列,可以识别目标字符。在本文中,表明在Farwell-Donchin范式中存在人为感知错误。为了消除此错误,提出了一种新的基于区域的范例。通过实验结果表明,新范式具有比Farwell-Donchin范式更多的优势,并具有更好的准确性。

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