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Computational Intelligence and Neuroscience
Volume 2017 (2017), Article ID 9528097, 6 pages
https://doi.org/10.1155/2017/9528097
Research Article

An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300

1College of Information Science and Technology, Jinan University, Guangzhou 510632, China
2School of Automation Science and Engineering, South China University of Technology and Guangzhou Key Laboratory of Brain Computer Interaction and Applications, Guangzhou 510640, China
3Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China

Correspondence should be addressed to Jinyi Long

Received 21 August 2016; Revised 8 November 2016; Accepted 12 December 2016; Published 19 February 2017

Academic Editor: Feng Duan

Copyright © 2017 Jinyi Long et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Jinyi Long, Jue Wang, and Tianyou Yu, “An Efficient Framework for EEG Analysis with Application to Hybrid Brain Computer Interfaces Based on Motor Imagery and P300,” Computational Intelligence and Neuroscience, vol. 2017, Article ID 9528097, 6 pages, 2017. doi:10.1155/2017/9528097