文献类型：期刊文献

英文题名：A new hybrid BCI paradigm based on P300 and SSVEP

作者：Wang, Minjue[1];Daly, Ian[2];Allison, Brendan Z.[3];Jin, Jing[1];Zhang, Yu[1];Chen, Lanlan[1];Wang, Xingyu[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Univ Reading, Sch Syst Engn, Brain Embodiment Lab, Reading, Berks, England;[3]Univ Calif San Diego, Dept Cognit Sci, Cognit Neurosci Lab, La Jolla, CA 92093 USA

年份：2015

卷号：244

起止页码：16

外文期刊名：JOURNAL OF NEUROSCIENCE METHODS

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000353754900004)】；

基金：This work was supported in part by the Grant National Natural Science Foundation of China, under Grant numbers 61203127, 61074113, 61105122, 61201124 and 61305028 and supported part by Shanghai Leading Academic Discipline Project, Project Number: B504. This work was also supported by the Fundamental Research Funds for the Central Universities (WG1414005, WH1314023).

语种：英文

外文关键词：Brain-computer interface (BCI); Hybrid paradigm; P300; SSVEP

摘要：Background: P300 and steady-state visual evoked potential (SSVEP) approaches have been widely used for brain-computer interface (BCI) systems. However, neither of these approaches can work for all subjects. Some groups have reported that a hybrid BCI that combines two or more approaches might provide BCI functionality to more users. Hybrid P300/SSVEP BCIs have only recently been developed and validated, and very few avenues to improve performance have been explored. New method: The present study compares an established hybrid P300/SSVEP BCIs paradigm to a new paradigm in which shape changing, instead of color changing, is adopted for P300 evocation to decrease the degradation on SSVEP strength. Result: The result shows that the new hybrid paradigm presented in this paper yields much better performance than the normal hybrid paradigm. Comparison with existing method: A performance increase of nearly 20% in SSVEP classification is achieved using the new hybrid paradigm in comparison with the normal hybrid paradigm. All the paradigms except the normal hybrid paradigm used in this paper obtain 100% accuracy in P300 classification. Conclusions: The new hybrid P300/SSVEP BCIs paradigm in which shape changing, instead of color changing, could obtain as high classification accuracy of SSVEP as the traditional SSVEP paradigm and could obtain as high classification accuracy of P300 as the traditional P300 paradigm. P300 did not interfere with the SSVEP response using the new hybrid paradigm presented in this paper, which was superior to the normal hybrid P300/SSVEP paradigm. (C) 2014 Elsevier B.V. All rights reserved.