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Fig. 5 | Journal of NeuroEngineering and Rehabilitation

Fig. 5

From: Electroencephalography-based endogenous brain–computer interface for online communication with a completely locked-in patient

Fig. 5

Results of the offline experiment. a Riemannian distance to the Riemannian mean of two class-related mean covariance matrices for LMI and MS. Each symbol represents a single 5-s trial and the dashed line indicates a decision border. This scatter plot was drawn after leave-one-out cross validation (LOOCV). b The average (cross-validated) classification accuracies of classifications for different combinations of three mental tasks: MS, LMI, and TMI. Nineteen electrodes were used for the classification. Each bar shows the average of the classification accuracies by different classification algorithms: Riemannian geometry (RG), linear discriminant analysis (LDA), and support vector machine (SVM). c The accuracies of classifying LMI and MS, evaluated using the three different classification methods. Nineteen electrodes were used. d The average offline classification accuracies with respect to the number of electrodes when RG was used for the classification. The classification accuracies were evaluated for all possible combinations of electrodes and then averaged

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