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Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition
2013
IEEE transactions on neural systems and rehabilitation engineering
Brain electrical activity recorded via electroencephalogram (EEG) is the most convenient means for brain-computer interface (BCI), and is notoriously noisy. The information of interest is located in well defined frequency bands, and a number of standard frequency estimation algorithms have been used for feature extraction. To deal with data nonstationarity, low signal-to-noise ratio, and closely spaced frequency bands of interest, we investigate the effectiveness of recently introduced
doi:10.1109/tnsre.2012.2229296
pmid:23204288
fatcat:2ejtmm3zbjb2nloyrvmkbmlw7u