## 3 Experiments and Results
### New Combinations of Signals Using Four Common Methods
#### 3.3.2 FbCSP Using New Combinations of Signals  
In this subsection, the tables' results are based on new combinations of signals. For comparison, two classifiers were used for all subjects. The minimum and maximum selected feature numbers are 5 and 40. Table 8 lists the average accuracies and kappa values for subjects with selected features and LDA and KNN classifiers. Table 9 lists the number of selected features checked for subjects with the LDA and KNN classifiers. In the following, the tables in this section are briefly described.  
Table 8 is related to the selection of features from all features of new combinations of signals for the classification of the left and right hands. Table 8 shows the two best-performing classifiers, LDA and KNN. Using Table 8, 25 features were selected as the number of best features for LDA and KNN classifiers, which have kappa values of 68.13% and 73.15%. But the accuracy difference between the numbers of feature selections varies within 1%. This is the effectiveness of using many features that have little effect on the  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Subject** & **FB\({}^{1}\) 1 and 2** & **FB4 and 5** & **FB4 and 6** & **FB4 and 7** & **FB4 and 8** & **FB1 and 9** & **FB2 and 9** & **FB3 and 9** & **FB4 and 9** \\ \hline S1 & 94.71 & 96.57 & 94.64 & 95.93 & 95.79 & 95.43 & 95.5 & 96.42 & 95.21 \\ S2 & 92.57 & 94.64 & 93.50 & 94.64 & 93.64 & 93.71 & 94.79 & 94.04 & 95.50 \\ S3 & 86.64 & 87.71 & 91.36 & 92.00 & 94.86 & 94.79 & 95.00 & 94.78 & 94.57 \\ S4 & 92.79 & 92.71 & 94.79 & 95.71 & 97.86 & 97.86 & 97.86 & 97.86 & 97.86 \\ S5 & 95.64 & 98.29 & 95.57 & 94.21 & 94.36 & 94.29 & 95.71 & 96.38 & 95.79 \\ Average & 92.47 & 93.99 & 93.97 & 94.50 & 95.30 & 95.21 & 95.77 & **95.90** & 95.79 \\ \(p\)-value & 0.0060 & 0.0053 & 0.0061 & 0.0065 & 0.0067 & 0.0066 & 0.0060 & 0.0061 & 0.0058 \\ \hline \hline \end{tabular}  
* FB I and J mean filter bank I and filter bank J. The \(p\)-values are from paired \(t\)-tests between results of CSP (C3, C4, CZ) [44] and new signals (FB I with J) on the left and right hands.  
\end{table}
Table 6: Kappa values with LDA classifier of hybrid signals from hand and foot with 10 features (m = 5).  
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Classifier Type** & **FB\({}^{1}\) 1** & **FB4** & **FB4** & **FB4** & **FB4** & **FB4** & **FB1 and 9** & **FB2 and 9** & **FB3 and 9** & **FB4 and 9** \\ \hline KNN\_Class\_Left & 88.83 & 90.18 & 91.11 & 91.39 & **92.18** & 90.16 & 92.03 & 92.72 & 92.30 \\ \hline KNN\_Class\_Right & 89.93 & 90.28 & 90.88 & 91.37 & **91.88** & 91.23 & 92.64 & 92.32 & 91.95 \\ \hline LDA\_Class\_Left & 93.48 & 94.02 & 93.86 & 93.81 & **93.99** & 94.31 & 94.15 & 94.33 & 94.09 \\ \hline LDA\_Class\_Right & 91.90 & 93.23 & 93.02 & 93.36 & **93.60** & 93.76 & 93.99 & 94.15 & 94.46 \\ \hline \hline \end{tabular}  
* FB I and J mean filter bank I and filter bank J.  
\end{table}
Table 7: Average sensitivity values of three classifiers using hybrid signals from hand and foot with 10 features.  
accuracy. The selection of the best features from all of the new combinations of signals could improve kappa by 5% in the second model compared to the first model in the best state.  
Table 9 shows the best average kappa values for subjects with KNN classifiers for the right and left hands. The highest kappa with the selection of 25 features is 73.15% for KNN. The maximum and minimum kappa values are for Subjects 8 and 3 and Subjects 2 and 4, with the largest difference. The \(p\)-values for all of the cases are between 0.0039 and 0.0042. This means that they are significant (\(p\)-value \(<\) 0.05).