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The Self-Face Paradigm Improves the Performance of the P300-Speller System
Frontiers in Computational Neuroscience ( IF 3.2 ) Pub Date : 2020-01-15 , DOI: 10.3389/fncom.2019.00093
Zhaohua Lu 1 , Qi Li 1 , Ning Gao 1 , Jingjing Yang 1
Affiliation  

Objective: 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. Methods: 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. Results: 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 (P < 0.05). Similar results were found for information transfer rates (P < 0.05). Conclusions: 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.

中文翻译:

Self-Face 范式提高了 P300-Speller 系统的性能

目的:之前的研究表明,名脸P300-speller的性能优于经典的行/列闪烁P300-speller。此外,在一些研究中,大脑在对自己的面孔做出反应时比对名人面孔更活跃,并且自我面孔刺激比名人面孔更能引发更大振幅的事件相关电位 (ERP)。因此,我们旨在以著名的人脸 P300-拼写器范式作为控制范式,研究自脸范式对进一步提高 P300-拼写器系统性能的作用。方法:我们设计了两个面部P300-speller范式,基于自脸和一个中性表情的名人脸(姚明,体育明星;名人脸拼写范式)。结果:在 340 到 480 ms (P300)、480 到 600 ms (P600f) 和额中央区从 700 到 800 的顶叶区域,自我面孔的 ERP 幅度明显大于著名的面部拼写范式小姐。离线和在线分类结果表明,自我人脸拼写范式的准确率在前两次叠加时均显着高于名人人脸拼写范式(P < 0.05)。信息传输率也有类似的结果(P < 0.05)。结论:自脸拼写范式显着提高了 P300 拼写系统的性能。这对于脑机接口(BCI)具有重要的实际应用,并且可以避免因使用他人面部图像而导致的侵权问题。从 480 到 600 ms (P600f),在额中央区域从 700 到 800 ms。离线和在线分类结果表明,自我人脸拼写范式的准确率在前两次叠加时均显着高于名人人脸拼写范式(P < 0.05)。信息传输率也有类似的结果(P < 0.05)。结论:自脸拼写范式显着提高了 P300 拼写系统的性能。这对于脑机接口(BCI)具有重要的实际应用,并且可以避免因使用他人面部图像而导致的侵权问题。从 480 到 600 ms (P600f),在额中央区域从 700 到 800 ms。离线和在线分类结果表明,自我人脸拼写范式的准确率在前两次叠加时显着高于著名人脸拼写范式(P < 0.05)。信息传输率也有类似的结果(P < 0.05)。结论:自脸拼写范式显着提高了 P300 拼写系统的性能。这对于脑机接口(BCI)具有重要的实际应用,并且可以避免因使用他人面部图像而导致的侵权问题。离线和在线分类结果表明,自我人脸拼写范式的准确率在前两次叠加时均显着高于名人人脸拼写范式(P < 0.05)。信息传输率也有类似的结果(P < 0.05)。结论:自脸拼写范式显着提高了 P300 拼写系统的性能。这对于脑机接口(BCI)具有重要的实际应用,并且可以避免因使用他人面部图像而导致的侵权问题。离线和在线分类结果表明,自我人脸拼写范式的准确率在前两次叠加时均显着高于名人人脸拼写范式(P < 0.05)。信息传输率也有类似的结果(P < 0.05)。结论:自脸拼写范式显着提高了 P300 拼写系统的性能。这对于脑机接口(BCI)具有重要的实际应用,并且可以避免因使用他人面部图像而导致的侵权问题。
更新日期:2020-01-15
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