In sum, it is an effective method to implement working memory task-based BCI based on cognitive impairment. We applied the preprocessing algorithm combining ICA and OEMD to extract more informative features and also applied the recognition algorithm combining SVM and GP to discover better kernels to improve the classification accuracy. This study provides theoretical and experimental basis of the quantity diagnosis for cognitive impairment. It is helpful for the intelligent identification of cognitive function and appropriate rehabilitation training.
