## 3 Results
### Comparison of Kinematics Data before and after Exercise Training in the Robo and Human Groups  
Table 2 and Figure 3 show the comparison of the kinematics data before and after practice for the Robo and Human groups. The main effect before and after practice was observed on the peak angle ratio during elbow extension using SAMO (\(p\) = 0.019, \(\eta^{2}\) = 0.027). However, for other items, there were no main effects or interactions between groups before and after practice. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Table (n = 13)** & \begin{tabular}{c} **Human (n = 12)** \\ \end{tabular} & \
\begin{tabular}{c} **Repeated Measures of ANOVA** \\ \end{tabular} \\ \cline{2-2} \cline{4-4} \multicolumn{1}{c}{**Variables**} & **Pre** & **Post** & **Pre** & **Post** \\ \cline{3-4} \cline{6-10}  & & & & **\#/1** & **\#/2** & **F** \\ \hline \multirow{4}{*}{
\begin{tabular}{c} Peak \\ velocity (deg/s) \\ Peak angle \\ ratio (\%) \\ Movement time (s) \\ \end{tabular} } & \multirow{4}{*}{\(101.0\pm 53.4\)} & \multirow{4}{*}{\(90.2\pm 37.3\)} & \multirow{4}{*}{\(107.2\pm 23.7\)} & \multirow{4}{*}{\(97.4\pm 30.5\)} & \multirow{4}{*}{\(1\)} & \multirow{4}{*}{\(23\)} & \multirow{4}{*}{\(0.644\)} & \multirow{4}{*}{\(0.008\)} & \multirow{4}{*}{\(1\)} & \multirow{4}{*}{\(23\)} & \multirow{4}{*}{\(3.77\)} & \multirow{4}{*}{\(0.064\)} & \multirow{4}{*}{\(0.019\)} & \multirow{4}{*}{\(0.926\)} \\ \cline{3-4} \cline{6-10}  & Peak angle & & & & & & & & & \\ \cline{3-4} \cline{6-10}  & ratio (\%) & & & & & & & & & \\ \cline{3-4} \cline{6-10}  & Movement time (s) & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparisons of kinematics data in manual therapy pre- and post-implementation of different methods of exercises. Figure 3: Multiple comparison of features of therapeutic motion techniques before and after exercise with different exercise methods. (**A**) Peak flexion velocity; (**B**) peak flexion angle ratio; (**C**) flexion movement time; (**D**) peak extension velocity; (**E**) peak extension angle ratio; (**F**) extension movement time. Blue dots: Robo group (n = 13); red dots: Human group (n = 12). Blue-outlined circles: mean values of the Robo group; red-outlined circles: mean values of the Human group; vertical bars: standard deviation. Blue solid line: the slope between the pre- and post-intervention values in the Robo group; red solid line: the slope between the pre- and post-intervention values in the Human group. Creation of Identifiers Using Machine Learning and Assessment of the Effect of Therapeutic Motion Technique  
Figure 4 shows the diagram obtained by creating identifiers using machine learning for exercise therapy techniques among students and therapists. Based on identifiers created by machine learning, among the students who had not practiced therapeutic motion techniques, one (7.7%) student in the Robo group and 0 (0.0%) students in the Human group were judged to be at a level similar to the therapists in terms of therapeutic motion techniques, indicating that many students did not possess sufficient skills before practice. Similar results were obtained using the SVM and RF algorithms. Using SVM, five (38.5%) students in the Robo group and 0 (0.0%) students in the Human group were judged to be at a level similar to that of the therapists in terms of exercise therapy techniques. Using RF, seven (53.8%) students in the Robo group and 0 (0.0%) students in the Human group were determined to be at a level similar to therapists in exercise therapy techniques. Compared to the Human group, the Robo group had significantly more students who were judged to have similar therapeutic motion techniques to the therapists (Table 3). For the SVM and RF classifiers, after supervised learning was conducted, accuracy was assessed using test data. The results confirmed an accuracy of 1.000 for SVM and 0.889 for RF.