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自我面孔范式提高了P300拼写器系统的性能。

The Self-Face Paradigm Improves the Performance of the P300-Speller System.

作者信息

Lu Zhaohua, Li Qi, Gao Ning, Yang Jingjing

机构信息

School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China.

出版信息

Front Comput Neurosci. 2020 Jan 15;13:93. doi: 10.3389/fncom.2019.00093. eCollection 2019.

Abstract

Previous studies have shown that the performance of the famous face P300-speller was better than that of the classical row/column flashing P300-speller. Furthermore, in some studies, the brain was more active when responding to one's own face than to a famous face, and a self-face stimulus elicited larger amplitude event-related potentials (ERPs) than did a famous face. Thus, we aimed to study the role of the self-face paradigm on further improving the performance of the P300-speller system with the famous face P300-speller paradigm as the control paradigm. We designed two facial P300-speller paradigms based on the self-face and a famous face (Ming Yao, a sports star; the famous face spelling paradigm) with a neutral expression. ERP amplitudes were significantly greater in the self-face than in the famous face spelling paradigm at the parietal area from 340 to 480 ms (P300), from 480 to 600 ms (P600f), and at the fronto-central area from 700 to 800 ms. Offline and online classification results showed that the self-face spelling paradigm accuracies were significantly higher than those of the famous face spelling paradigm at superposing first two times ( < 0.05). Similar results were found for information transfer rates ( < 0.05). The self-face spelling paradigm significantly improved the performance of the P300-speller system. This has significant practical applications for brain-computer interfaces (BCIs) and could avoid infringement issues caused by using images of other people's faces.

摘要

先前的研究表明,著名面孔P300拼写器的性能优于经典的行/列闪烁P300拼写器。此外,在一些研究中,大脑对自己的面孔做出反应时比面对著名面孔时更活跃,并且自我面孔刺激引发的事件相关电位(ERP)幅度比著名面孔更大。因此,我们旨在以著名面孔P300拼写器范式作为对照范式,研究自我面孔范式对进一步提高P300拼写器系统性能的作用。我们基于自我面孔和一张著名面孔(体育明星姚明;著名面孔拼写范式)设计了两种面部P300拼写器范式,面部表情均为中性。在顶叶区域,从340至480毫秒(P300)、从480至600毫秒(P600f)以及额中央区域从700至800毫秒时,自我面孔条件下的ERP波幅显著大于著名面孔拼写范式。离线和在线分类结果显示,在前两次叠加时,自我面孔拼写范式的准确率显著高于著名面孔拼写范式(<0.05)。信息传输率也有类似结果(<0.05)。自我面孔拼写范式显著提高了P300拼写器系统的性能。这对脑机接口(BCI)具有重要的实际应用价值,并且可以避免因使用他人面部图像而引发的侵权问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4eb0/6974691/0d441fd4a943/fncom-13-00093-g0001.jpg

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