— A major challenge in applying machine learning methods to Brain-Computer Interfaces (BCIs) is to overcome the on-line non-stationarity of the data blocks. An effective BCI syst...
Qibin Zhao, Liqing Zhang, Andrzej Cichocki, Jie Li
Common Spatial Pattern (CSP) is widely used in discriminating two classes of EEG in Brain Computer Interface applications. However, the performance of the CSP algorithm is affecte...
Mahnaz Arvaneh, Cuntai Guan, Kai Keng Ang, Hiok Ch...
In this paper, we propose a new algorithm for BrainComputer Interface (BCI): the Spatially Regularized Common Spatial Patterns (SRCSP). SRCSP is an extension of the famous CSP alg...
Brain-Computer Interfaces can suffer from a large variance of the subject conditions within and across sessions. For example vigilance fluctuations in the individual, variable ta...
Benjamin Blankertz, Motoaki Kawanabe, Ryota Tomiok...
Brain-Computer Interfaces (BCIs) allow a user to control a computer application by brain activity as acquired, e.g., by EEG. A standard step in a BCI system is to project the EEG ...
Wojciech Wojcikiewicz, Carmen Vidaurre, Motoaki Ka...