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. 2015 Oct 16;3:2100108. doi: 10.1109/JTEHM.2015.2485261

TABLE 4. BCI Classification Performance Comparison of the Proposed Algorithm Against State-of-the-Art Methods.

L1b K3b K6b Avg
Hill & Schröder [26] (resampling 100Hz, detrending, Informax ICA, Welch amplitude spectra, PCA, SVM, validation on a test dataset) 64.17 96.11 55.83 72.03
Guan, Zhang & Li [26] (Fisher ratios of channel frequency-time bins, feature selection, mu and beta band, CSP, SVM, validation on test dataset) 85.00 86.67 81.67 84.44
Gao, Wu & Wei [26] (surface Laplacian, 8–30Hz filter, multi-class CSP, SVM+kNN+LDA, validation on a test dataset) 78.33 92.78 57.50 76.20
Koprinska [34] (CSP, 3 frequency bands, 7 features extracted, feature selection, validation using holdout method (50 %)) 78.33 94.44 62.50 78.42
Wentrup et al. [35] (ITFE, logistic regression classifier with L1-regularization, validation using holdout method-10 trials from each class were used for testing) 78.60 94.20 69.00 80.60
Wentrup et al. [36] (LCMV, logistic regression classifier) with L1-regularization, validation using holdout method-10 trials from each class were used for testing) 78.40 93.40 62.9 78.23
Wentrup et al. [36] (ICA, logistic regression classifier with L1-regularization, validation using holdout out method-10 trials from each class were used for testing; 78.90 93.40 62.90 78.40
Schlögl et al. [7] (AAR (3), SVM, Leave-one-out cross validation) 53.90 77.2 52.4 61.16
Proposed (LP-SVD, logistic model tree) (without the Q and the Hotelling's Inline graphic statistics, 10 fold cross validation) 69.16 86.11 69.58 74.95
Proposed (LP-SVD, logistic model tree) (including the Q and the Hotelling's Inline graphic statistics, 10 fold cross validation) 77.91 90.00 76.25 81.38