Chen Long, Jin Jing, Zhang Yu, Wang Xingyu, Cichocki Andrzej
Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, PR China.
Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, PR China.
J Neurosci Methods. 2015 Jan 15;239:18-27. doi: 10.1016/j.jneumeth.2014.10.002. Epub 2014 Oct 12.
It was proved that the human face stimulus were superior to the flash only stimulus in BCI system. However, human face stimulus may lead to copyright infringement problems and was hard to be edited according to the requirement of the BCI study. Recently, it was reported that facial expression changes could be done by changing a curve in a dummy face which could obtain good performance when it was applied to visual-based P300 BCI systems.
In this paper, four different paradigms were presented, which were called dummy face pattern, human face pattern, inverted dummy face pattern and inverted human face pattern, to evaluate the performance of the dummy faces stimuli compared with the human faces stimuli.
COMPARISON WITH EXISTING METHOD(S): The key point that determined the value of dummy faces in BCI systems were whether dummy faces stimuli could obtain as good performance as human faces stimuli. Online and offline results of four different paradigms would have been obtained and comparatively analyzed.
Online and offline results showed that there was no significant difference among dummy faces and human faces in ERPs, classification accuracy and information transfer rate when they were applied in BCI systems.
Dummy faces stimuli could evoke large ERPs and obtain as high classification accuracy and information transfer rate as the human faces stimuli. Since dummy faces were easy to be edited and had no copyright infringement problems, it would be a good choice for optimizing the stimuli of BCI systems.
在脑机接口（BCI）系统中，已证明人脸刺激优于仅闪光刺激。然而，人脸刺激可能会导致版权侵权问题，并且难以根据BCI研究的要求进行编辑。最近，有报道称可以通过改变虚拟人脸中的一条曲线来实现面部表情变化，将其应用于基于视觉的P300 BCI系统时能获得良好性能。
本文提出了四种不同的范式，即虚拟人脸模式、真实人脸模式、倒置虚拟人脸模式和倒置真实人脸模式，以评估虚拟人脸刺激与真实人脸刺激相比的性能。
决定虚拟人脸在BCI系统中价值的关键点在于虚拟人脸刺激是否能获得与真实人脸刺激一样好的性能。已获取并对四种不同范式的在线和离线结果进行了比较分析。
在线和离线结果表明，当将虚拟人脸和真实人脸应用于BCI系统时，它们在事件相关电位（ERPs）、分类准确率和信息传递率方面没有显著差异。
虚拟人脸刺激能够诱发较大的事件相关电位，并且能获得与真实人脸刺激一样高的分类准确率和信息传递率。由于虚拟人脸易于编辑且不存在版权侵权问题，它将是优化BCI系统刺激的一个不错选择。
