## 3 Experimental Results and Discussion
### Results of the Feature-Based Evaluation Procedure  
In this section, we present the results obtained for our proposed approach using the feature reduction procedure described in Section 2.7. Table 3 shows the average classification accuracies computed over all subjects for each of the 12 iterations of the feature reduction procedure. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Iterations of the**} & \multicolumn{4}{c}{**Elimated EEG Channel**} & \\ \multicolumn{4}{c}{**Channel Reduction**} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} & \multicolumn{4}{c}{} \\ \multicolumn{4}{c}{**Procedure**} & \(F_{7}\) & \(F_{7}\) & \(AF_{5}\) & \(O_{1}\) & \(F_{4}\) & \(F_{7}\) & \(AF_{5}\) & \(F_{8}\) & \(F_{3}\) & \(P_{8}\) & \(O_{2}\) & \(FC_{5}\) & \(T_{8}\) & \(FC_{6}\) \\ \hline \multirow{8}{*}{Average classification accuracy(\%)} & Iteration 1 & 83.76 & 83.53 & 83.69 & 83.82 & 84.08 & 83.59 & 83.89 & 83.78 & 84.11 & 84.15 & 83.93 & 84.23 & 83.59 & 84.33 \\ \cline{2-11}  & Iteration 2 & 83.19 & 82.98 & 82.96 & 83.55 & 83.29 & 83.27 & 83.42 & 82.82 & 83.24 & 83.20 & 83.75 & 83.60 & 83.76 \\ \cline{2-11}  & Iteration 3 & 81.83 & 82.18 & 82.13 & 82.43 & 82.52 & 82.40 & 82.11 & 82.07 & 82.40 & 82.61 & 82.55 & 82.63 & \\ \cline{2-11}  & Iteration 4 & 81.60 & 81.62 & 81.13 & 82.38 & 81.98 & 81.92 & 81.99 & 82.04 & 81.98 & 82.30 & 82.57 & \\ \cline{2-11}  & Iteration 5 & 80.81 & 81.22 & 80.88 & 81.30 & 81.37 & 81.32 & 81.51 & 81.44 & 81.59 & 81.72 & \\ \cline{2-11}  & Iteration 6 & 80.54 & 80.37 & 79.11 & 80.43 & 80.86 & 80.68 & 80.57 & 80.84 & 81.08 & \\ \cline{2-11}  & Iteration 7 & 78.98 & 79.83 & 72.86 & 79.71 & 79.66 & 79.64 & 79.75 & 79.98 & & & & & \\ \cline{2-11}  & Iteration 8 & 77.58 & 72.87 & 77.75 & 78.26 & 78.10 & 78.24 & 78.72 & & & & & & & \\ \cline{2-11}  & Iteration 9 & 75.70 & 76.27 & 76.29 & 76.31 & 76.46 & 76.96 & & & & & & & & \\ \cline{2-11}  & Iteration 10 & 74.20 & 74.86 & 74.29 & 74.75 & 75.34 & & & & & & & & & \\ \cline{2-11}  & Iteration 11 & 71.41 & 71.69 & 72.06 & 72.23 & & & & & & & & & & & \\ \cline{2-11}  & Iteration 12 & 68.32 & 69.20 & 71.01 & & & & & & & & & & & & \\ \cline{2-11}  & Iteration 13 & 65.08 & 65.90 & & & & & & & & & & & & & & \\ \hline \multicolumn{11}{c}{} & Iteration 14 & 65.90 & & & & & & & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The mean values of the average classification accuracies computed for each iteration of the channel reduction procedure over all subjects. Specifically, at the first iteration, eliminating feature \(TF_{8}\) provides an average classification accuracy of 86.63%, which is higher than the average classification accuracies obtained when any of the other 11 time-frequency features is eliminated. In the second iteration, the additional elimination of the feature \(TF_{3}\) provides an average classification accuracy of 87.68, which is higher than the average classification accuracies obtained when eliminating any of the remaining 10 time-frequency features. Moreover, in the subsequent iterations of the feature reduction procedure, the average classification accuracy keeps increasing until the 9 th iteration, at which the average classification accuracy achieved using the time-frequency features \(TF_{7}\), \(TF_{9}\), and \(TF_{12}\) is 89.24%. In the consecutive iterations, the average classification accuracy starts to decrease after each iteration. Finally, at the last iteration, an average classification accuracy of 87.06% is achieved using the time-frequency feature \(TF_{7}\).