## 3 Results  
### Performance Validation Results of the Simulator  
To validate the performance of the maxillofacial reconstruction surgery simulator, the reconstruction process was carried out on a PC connected to an HMD, and the metric \begin{table}
\begin{tabular}{c c c} \hline \hline \multicolumn{2}{c}{**Category**} & \multicolumn{1}{c}{**Question**} \\ \hline \multirow{4}{*}{VR Simulator} & Q (1) & Does the simulator appropriately implement the 3D model based on patient data? \\  & Q (2) & Is the 3D model displayed clearly in the simulator? \\  & Q (3) & Does the 3D model remain clear while other functions are being performed? \\  & Q (4) & Do the functions performed in the simulator operate with precision? \\  & Q (5) & Do the viewpoint and hand position in the simulator align accurately? \\ \hline \multirow{3}{*}{Usability} & Q (1) & Does the simulator operate properly according to the user’s intent? \\  & Q (2) & Is the simulator’s operation method user-friendly? \\  & Q (3) & Is the UI/UX well-designed to be user-friendly? \\ \hline \multirow{3}{*}{Expertise} & Q (1) & Do you think the simulator demonstrates a level of expertise? \\  & Q (2) & Is the simulator similar to actual guide creation software? \\  & Q (3) & Can the simulator generate guides that could be applied to the actual surgical process? \\ \hline \multirow{3}{*}{Educational usefulness} & Q (1) & Does the guide creation process in the simulator help in understanding maxillofacial reconstruction surgery using the iliac bone? \\  & Q (2) & Can this simulator be used to explain the procedure to other medical professionals? \\ \cline{1-1}  & Q (3) & Can this simulator be used to explain the procedure to patients? \\ \cline{1-1}  & Q (4) & Would you be willing to use this simulator as a basis for creating other simulators? \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Questionnaire categories for simulator evaluation. values were recorded based on each evaluation method. The recorded values were then compiled to calculate the average values for the performance evaluation metrics. Figure 10 shows graphs of the recorded values for each performance evaluation metric, and Table 6 shows the average values of the performance evaluation metrics. The FPS measurement results showed an average value of 69.91, a minimum value of 36.15, and a maximum value of 73.96. These results indicate that stable frames were maintained, excluding resource-intensive tasks such as model-data processing, cutting, and exporting. Even during resource-intensive tasks, there were no severe frame drops or prolonged frame decreases that would cause noticeable discomfort. This implies that \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Item** & **Average** & **Item** & **Average** \\ \hline FPS & 69.91 (fps) & Memory usage & 449.38 (MB) \\ CPU usage & 9.09 (\%) & Resection time & 3.11 (s) \\ GPU usage & 8.85 (\%) & Recognition accuracy & 97.6 (\%) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Average values for each performance evaluation metric. Figure 10: Graphs of the recorded performance evaluation metric results: **(a)** FPS; **(b)** CPU usage; (c) GPU usage; **(d)** memory usage; **(e)** resection time; and **(f)** recognition accuracy. the simulator operates stably without significant frame fluctuations that could affect user experience, suggesting that the reconstruction surgery process can be performed in a smooth environment. The resource usage measurement results showed that CPU usage had an average value of 9.09%, a minimum value of 4.00%, and a maximum value of 15.0%. GPU usage had an average value of 8.85%, a minimum value of 4.00%, and a maximum value of 13.5%. Memory usage was recorded at an average of 449.38 MB, with a minimum of 410 MB and a maximum of 505 MB. The fact that the CPU and GPU average usage values are below 10% indicates that the simulator effectively utilizes central and graphical processing resources, optimizing various computations and graphic processing to ensure stable device operation.