## 6 CMC Tracking Device and System Evaluation
### Results and Discussion  
The performance of the tracking device was evaluated by two able\(-\)bodied volunteers. The proposed methodology was evaluated by one volunteer. The measured thumb parameters for each volunteer were used as inputs to the mapping algorithm and are presented in Table 3.  
During the device operation test, each volunteer easily personalized the tracking device and calibrated the system with guidance from a research team member. The tracking device captured the CMC joint motion of both volunteers. During visual verification, the \(R_{cmc}\) was observed to follow the tracked thumb circumduction motion for both volunteers. The \(H_{cmc}\), mapped \(H_{cmc}\), and estimated \(R_{cmc}\) positions during the thumb circumduction for Volunteer 1 are shown in Figure 8. Subsequently, using the system, each volunteer was able to telemanipulate the ARH (with only \(R_{cmc}\)) to successfully oppose the cylinder against the palm, as shown in Figure 9.  
The framework validation test was performed by Volunteer 1, who successfully telemanipulated the ARH to perform the prescribed thumb poses and grasp different shaped objects, as shown in Figure 10. The prescribed poses performed by the volunteer are shown in Figure 10a\(-\)d. The power grasps for a cylinder and a cuboid are shown in Figure 10e and Figure 10f, respectively. The precision grasps for a marker pen (thin cylinder) and a sphere are shown in Figure 10g and h, respectively. The trajectory of poses during the telemanipulation of the ARH by Volunteer 1 to grasp a cylinder (diameter of 40 mm and height of 120 mm) is shown in Figure 11, and the trajectory of the robot thumb joint angles is shown in Figure 12.  
The experimental results of the device operation tests verify that the developed tracking device could be easily personalized and calibrated to volunteers with different thumb dimensions and successfully track their CMC joint motion. Using the RPA algorithm, the estimated \(H_{cmc}\) motion was mapped to the \(R_{cmc}\) to position and oppose an object against the palm by each volunteer.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Volunteer** & \multicolumn{3}{c}{**Philange Length *} & \multicolumn{3}{c}{**Thickness *} & \multicolumn{3}{c}{**Range of Motion **} \\ \cline{2-7}  & \(\mathbf{L_{mp}}\) & \(\mathbf{L_{pp}}\) & \(\mathbf{L_{dp}}\) & \(\mathbf{MCP}\) & \(\mathbf{\theta_{FE}}\) & \(\mathbf{\theta_{AA}}\) \\ \hline
1 & 52 & 45 & 34 & 20 & 45 & 50 \\
2 & 48 & 35 & 27 & 15 & 55 & 50 \\ \hline \hline \end{tabular}  
* All length dimensions are in millimeters (mm). ** All angular dimensions are in degrees (deg).  
\end{table}
Table 3: Measured thumb parameters for each volunteer.  
According to the framework verification test results, the tracking device integrated with the developed system following the proposed framework could be successfully deployed to telemanipulate a robot thumb with kinematic differences. The results validate the proposed framework and its ability to integrate functional components of the telemanipulation system by successfully reaching prescribed poses and performing various grasps (precision and power) of objects using the CMC tracking device.  
Figure 8: The trajectory/positions of \(H_{\textit{cmc}}\), mapped \(H_{\textit{cmc}}\), and estimated \(R_{\textit{cmc}}\) using the tracking device data captured during thumb circumduction by Volunteer 1. The hand model is not to scale but is shown to facilitate the understanding of the workspace orientation.  
Figure 9: Time–lapse images of the robot CMC joint controlled by the human CMC joint while opposing a cylinder against the palm by each volunteer.