文献类型：期刊文献

英文题名：Comparison of the BCI Performance between the Semitransparent Face Pattern and the Traditional Face Pattern

作者：Cheng, Jiao[1];Jin, Jing[1];Wang, Xingyu[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai, Peoples R China

年份：2017

卷号：2017

外文期刊名：COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE

收录：;EI(收录号：20171703612517);WOS:【SSCI(收录号:WOS:000405740900001)，SCI-EXPANDED(收录号:WOS:000405740900001)】；

基金：This work was supported in part by the Grant National Natural Science Foundation of China, under Grants nos. 61573142, 61203127, 91420302, and 61305028. This work was also supported by the Fundamental Research Funds for the Central Universities (WG1414005, WH1314023, and WH1516018).

语种：英文

外文关键词：Classification (of information) - Brain - Interfaces (computer) - Transparency

摘要：Brain-computer interface (BCI) systems allow users to communicate with the external world by recognizing the brain activity without the assistance of the peripheral motor nervous system. P300-based BCI is one of the most common used BCI systems that can obtain high classification accuracy and information transfer rate (ITR). Face stimuli can result in large event-related potentials and improve the performance of P300-based BCI. However, previous studies on face stimuli focused mainly on the effect of various face types (i.e., face expression, face familiarity, and multifaces) on the BCI performance. Studies on the influence of face transparency differences are scarce. Therefore, we investigated the effect of semitransparent face pattern (STF-P) (the subject could see the target character when the stimuli were flashed) and traditional face pattern (F-P) (the subject could not see the target character when the stimuli were flashed) on the BCI performance from the transparency perspective. Results showed that STF-P obtained significantly higher classification accuracy and ITR than those of F-P (p < 0.05).