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Electroencephalography (EEG) and brain-computer interfaces (BCI) are receiving increasing attention and expanding application in stroke study. To identify stroke patients and normal controls during mental rotation task, common spatial pattern (CSP) algorithm is employed to extract features from binary-class EEG which will be further to form the dictionary for sparse representation. In the classification...
In addition to the noisy and limited spatial resolution characteristics of the electroencephalography (EEG) signal, the intrinsic nonstationarity in the EEG data makes the single-trial EEG classification an even more challenging problem in brain–computer interface (BCI). Variations of the signal properties within a session often result in deteriorated classification performance. This is mainly attributed...
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