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不同矩阵大小诱发的事件相关电位:对脑机接口(BCI)系统的启示。

ERPs evoked by different matrix sizes: implications for a brain computer interface (BCI) system.

作者信息

Allison Brendan Z, Pineda Jaime A

机构信息

Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2003 Jun;11(2):110-3. doi: 10.1109/TNSRE.2003.814448.

Abstract

A brain-computer interface (BCI) system may allow a user to communicate by selecting one of many options. These options may be presented in a matrix. Larger matrices allow a larger vocabulary, but require more time for each selection. In this study, subjects were asked to perform a target detection task using matrices appropriate for a BCI. The study sought to explore the relationship between matrix size and EEG measures, target detection accuracy, and user preferences. Results indicated that larger matrices evoked a larger P300 amplitude, and that matrix size did not significantly affect performance or preferences.

摘要

脑机接口(BCI)系统可让用户通过从多个选项中选择其一进行通信。这些选项可以呈现在一个矩阵中。更大的矩阵允许使用更大的词汇量,但每次选择需要更多时间。在本研究中,要求受试者使用适合BCI的矩阵执行目标检测任务。该研究旨在探索矩阵大小与脑电图测量、目标检测准确性和用户偏好之间的关系。结果表明,更大的矩阵诱发更大的P300波幅,并且矩阵大小对性能或偏好没有显著影响。

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