## 4 Experiments and Results
### EEG-TCNTransformer with Different Hyperparameters  
The different number of filters \(k\) in the TCN block and number of TCN blocks \(T\) are validated to select the best hyperparameters. In Table 17, the average of all subjects is summarised with different \(k\) and \(T\). With each \(T\), the more filters \(k\), the higher the average accuracy, but the average accuracy stops increasing and decreases at a level of filters. With \(T=1\), the average accuracy is highest at \(k=60\). With \(T=2\), the average accuracy is highest at \(k=60\). With \(T=3\), the average accuracy is highest at \(k=70\). Overall, \(T=3\) and \(k=70\) produce the best average accuracy of 83.41%. The detailed accuracy of 9 subjects is in Table A5. In Table 18, the most improvement is seen in subject 2; EEG-TCNTransformer is higher than EEG-Conformer by about 10.95% and higher than EEG-TCNet by about 7.77%. Subject 6 and subject 9 of EEG-TCNTransformer are also more improved significantly than those of EEG-Conformer, by about 4.65% and 6.44%, respectively. Additionally, EEG-TCNTransformer improves subject 1 and subject 4 by about 3.91% and 3.95%, respectively. The average accuracy of EEG-TCNTransformer is 83.41% (confidence interval = 95.2%), which is higher by 3.77% than the average accuracy of EEG-Conformer and 6.86% than the average accuracy of EEG-TCNet. In Table 19, EEG-TCNTransformer improves subject 2 by about 11.16% compared with EEG-Conformer, but only higher by 2.59% than EEG-TCNet. Subject 9 of EEG-TCNTransformer has the highest improvement in precision, about 6.44% and 9.85% compared with EEG-Conformer and EEG-TCNet, respectively. Moreover, EEG-TCNTransformer \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{\(T\)} \\ \hline  & **1** & **2** & **3** \\ \hline
**10** & 75.85 & 76.52 & 76.16 \\ \hline
**20** & 76.78 & 79.04 & 78.86 \\ \hline
**30** & 80.57 & 80.99 & 82.06 \\ \hline
**40** & 80.40 & 81.60 & 82.81 \\ \hline
**50** & 79.32 & 81.96 & 82.75 \\ \hline
**60** & 81.44 & 82.68 & 81.63 \\ \hline
**70** & 81.12 & 82.57 & **83.41** \\ \hline
**80** & 81.28 & 82.18 & 81.30 \\ \hline
**90** & 80.96 & 81.81 & 81.78 \\ \hline
**100** & 80.49 & 82.13 & 81.25 \\ \hline \hline \end{tabular}
\end{table} 
Table 17: The average accuracy of different numbers of filters \(k\) and the number of TCN blocks \(T\). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Subject** & **EEG-TCNet** & **EEG-Conformer** & **EEG-TCNTransformer** \\  & & & **(Confidence Interval (\%))** \\ \hline
**S1** & 82.92 & 83.99 & **87.90** (95.48) \\
**S2** & 61.13 & 57.95 & **68.90** (93.59) \\
**S3** & 91.58 & **94.51** & **94.51** (98.36) \\
**S4** & 64.91 & 78.07 & **82.02** (94.64) \\
**S5** & 76.45 & 78.62 & **81.88** (93.59) \\
**S6** & 59.53 & 63.72 & **68.37** (93.04) \\
**S7** & **91.34** & 88.81 & 89.53 (95.87) \\
**S8** & 81.92 & 88.56 & **88.56** (96.59) \\
**S9** & 79.17 & 82.58 & **89.02** (95.68) \\
**Average** & 76.55 & 79.64 & **83.41** (95.20) \\ \hline \hline \end{tabular}
\end{table} 
Table 18: Comparisons in the accuracy EEG-TCNet baseline, EEG-Conformer baseline, and EEG-TCNTransformer. also improves the precision of subject 1, subject 4, subject 5, and subject 6 compared with both EEG-TCNet and EEG-Conformer. The average precision of EEG-TCNTransformer is 83.43%, which is higher by 3.77% than the average precision of EEG-Conformer and 4.36% than the average precision of EEG-TCNet. In Table 20, the recall of subject 2 of EEG-TCNTransformer is significantly higher than that of EEG-Conformer by 12.62% and higher than that of EEG-TCNet by 9.97%. Moreover, EEG-TCNTransformer improves the recall of subject 6 and subject 9 by about 6.49% and 5.28% compared with EEG-Conformer. Additionally, EEG-TCNTransformer also improves the recall of subject 1, subject 4, and subject 5. The average recall of EEG-TCNTransformer is 84.05%, which is higher by 3.89% than the average recall of EEG-Conformer and 7.49% than the average recall of EEG-TCNet.