## 7 Conclusions  
In this paper, a model of a compliant mechanism that is a counterpart to the human hand was discussed. For this purpose, compliant mechanisms are the perfect choice due to their properties and benefits compared with traditional mechanisms, such as no need for lubrication, no noise or oscillations, and wear caused by clearance in the joints. Therefore,  
Figure 14: Example of computer vision measured bending angle \(\theta\) for compliant finger with (**a**) curved flexure hinge with a 21-degree bend and (**b**) curved flexure hinge with a 90-degree bend, for a loaded 30 g weight. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Flexure Hinge**} & \multirow{2}{*}{**Method**} & \multicolumn{6}{c}{**Force (N)**} \\ \cline{3-8}  & & \(\approx\)**0.1** & \(\approx\)**0.2** & \(\approx\)**0.3** & \(\approx\)**0.4** & \(\approx\)**0.5** & \(\approx\)**0.6** \\ \hline \multirow{4}{*}{**Type**} & Computer Vision & \multirow{2}{*}{26.57\({}^{\circ}\)} & \multirow{2}{*}{33.18\({}^{\circ}\)} & \multirow{2}{*}{46.45\({}^{\circ}\)} & \multirow{2}{*}{68.01\({}^{\circ}\)} & \multirow{2}{*}{99.46\({}^{\circ}\)} & \multirow{2}{*}{124.81\({}^{\circ}\)} \\  & FEA & & & & & & & \\ \hline \multirow{4}{*}{**Type**} & Computer Vision & \multirow{2}{*}{26.34\({}^{\circ}\)} & \multirow{2}{*}{37.67\({}^{\circ}\)} & \multirow{2}{*}{51.34\({}^{\circ}\)} & \multirow{2}{*}{77.47\({}^{\circ}\)} & \multirow{2}{*}{108.12\({}^{\circ}\)} & \multirow{2}{*}{133.96\({}^{\circ}\)} \\  & FEA & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: New results for the bending angle \(\theta\) measured at the endpoint of compliant fingers. two types of compliant fingers were analyzed. Prototypes with curved flexure hinges of mentioned fingers were 3D-printed in order to experimentally prove which of these two types represents a more adequate solution. Such models can be used in various applications, such as robotic grasping devices that simulate the movements of a human hand, interactive video gaming, and hand rehabilitation [32]. In the case of hand rehabilitation, the discussed models could be used as parts of the hand exoskeletons for patients with impaired hand fingers' movements or parts of the \"movement training by imitation\" rehabilitation systems, where the patient would be asked to imitate the movement of the fingers' models teleoperated by the therapist or intelligently controlled to demonstrate particular movements of the figures and hand gestures. Presented simulations and parametric analyzes were performed to demonstrate the accuracy of the software analysis to correspond with the experimental results and, thus, to use this method for further research. The initially obtained results showed a poor correlation between experimental and FEA results. The assumption was made that the information provided by the material manufacturer was different from the filament used for 3D-printed prototypes of compliant fingers. This is a common mistake when experimenting with 3D-printed prototypes. As a solution, adequate measurements should be taken to obtain the correct specifications for 3D-printed compliant fingers and set the correct parameters for the FEA simulation. To demonstrate this possible solution, tensile test was performed to determine the material properties of the 3D-printed test specimens, which were used for the re-executed FEA. The newly obtained results showed a good correlation between experimental and FEA results. In the areas of low and medium deformations, the agreement of FEA and experimental results could be seen within the limits of less than 10%. The limit increases to 25% in regions with high deformations. This discrepancy can be attributed to the fact that the printed elements are often not of homogeneous structure, while the model obtained by simulation is completely idealized. It should also be emphasized that the program in which the analysis was performed does not provide optimal results related to the non-linear area of deformations.