# Donning/Doffing and Arm Positioning Influence in Upper Limb Adaptive Prostheses Control
## 3 Results  
### Donning and Doffing Experiment  
The obtained metrics (mean and variance) of the five donning/doffing experiments for each subject are shown in Table 1. They are shown graphically in a box and whisker plot in Figure 5.  
Figure 5 shows that the completion rate metric had a consistent high value for all subjects. In our previous work [49], we showed that the IIR adaptive algorithm had a 95% CR when the training and test armband position were the same. In this study, it was observed that the high completion rate was not diminished by the donning/doffing effect. Three participants achieved a median 100% accuracy, and the worst result was a value of 90% for subject #3 one day. Figure 5 also shows that the variance is small for all participants and metrics. It means that after training the first day, the system was robust enough to maintain the same performance the next days both in  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Participant** & **Completion Rate (\%)** & **Path Efficiency (\%)** & **Completion Time (s)** & **Attempt Ratio** \\ \hline
1 & 99.44 \(\pm\) 1.24 & 90.75 \(\pm\) 1.86 & 5.338 \(\pm\) 0.387 & 1.017 \(\pm\) 0.025 \\
2 & 97.78 \(\pm\) 3.62 & 87.20 \(\pm\) 1.95 & 5.554 \(\pm\)  
Only one participant showed a wider variance in path efficiency, subject #6. Looking into the time evolution of the results for that subject, we discovered a continuous learning trend during the experiment. This was the only patient that showed an accentuated learning behavior as the others kept a more robust performance. Analyzing our results in depth, Figure 6 shows the PE for subject #6 (blue line) compared to the average value of all participants (black line) vs. the test number. It reveals that the PE performance of subject #6 improved during the training sessions, while the other participants had a steady performance, with an approximately 84% PE value. Thus, his higher variance in the PE metric is not due to a lack of robustness but to a learning process. A repeated measures ANOVA (\(p<0.05\)) confirms that not one metric was changing with time, reassuring the robustness of the initial training: CR \(p=0.8397\), PE \(p=0.3152\), AR \(p=0.8096\) and CT \(p=0.5311\). To confirm the robust behavior, we run a MANOVA test that restates the results obtained with the previous ANOVA analysis: There was not statistically sufficient evidence to reject the hypothesis that all metrics come from the same distribution (\(p<0.05\)). Figure 5: Box and whisker plot for the Completion Rate (CR), Path Efficiency (PE), Attempt Ratio (AR) and Completion Time (CT) for each participant. Except for patient 6’s PE value, the rest of the boxes show a small variance. This is proof of a consistent behavior through time. The values in Figure 5 and Table 1 provide a visual and quantitative performance analysis of the adaptive filtering algorithm in donning/doffing experiments but do not show the dynamics of the experiments, i.e., the user experience. To show this behavior in a more intuitive and visual way, we included some videos where the dynamics of the system are appreciated.