# Measuring Quality of Service in a Robotized Comprehensive Geriatric Assessment Scenario
## 5 Experimental Evaluation
### Experiments in Real Scenarios
The minimum and the average differ slightly as the observations  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline  & & **G \#1** & **G \#2** & **G \#3** & **G \#4** & **G \#5** & **G \#6** & **G \#7** & **G \#8** & **G \#9** & **G \#10** & **G \#11** \\ \hline \multirow{4}{*}{**G**} & min & 0.4572 & 0.4984 & 0.5000 & 0.0002 & 0.4522 & 0.2958 & 0.5000 & 0.1241 & 0.4976 & 0.5000 & 0.1071 \\ \cline{2-11}  & max & 0.9120 & 0.9722 & 0.9822 & 0.5882 & 0.9109 & 0.9163 & 0.9822 & 0.9278 & 0.9701 & 0.9822 & 0.5882 \\ \cline{2-11}  & avg & 0.6800 & 0.7433 & 0.8204 & 0.1602 & 0.6774 & 0.6083 & 0.8191 & 0.5586 & 0.7482 & 0.8182 & 0.2647 \\ \cline{2-11}  & sd & 0.1122 & 0.1549 & 0.1364 & 0.2060 & 0.1133 & 0.1555 & 0.1366 & 0.2167 & 0.1494 & 0.1365 & 0.1423 \\ \cline{2-11}  & last & 0.9120 & 0.9722 & 0.9822 & 0.0003 & 0.9109 & 0.9163 & 0.9822 & 0.9278 & 0.9701 & 0.9822 & 0.4833 \\ \hline \multirow{4}{*}{**G**} & min & 0.5000 & 0.4984 & 0.5000 & 0.0017 & 0.5000 & 0.4854 & 0.5000 & 0.4978 & 0.4976 & 0.5000 & 0.4352 \\ \cline{2-11}  & max & 0.9999 & 1.0000 & 1.0000 & 0.5882 & 0.9998 & 0.9998 & 1.0000 & 1.0000 & 0.9999 & 1.0000 & 0.9861 \\ \cline{2-11}  & avg & 0.8946 & 0.8399 & 0.9094 & 0.2423 & 0.9003 & 0.8372 & 0.9081 & 0.8879 & 0.8514 & 0.9078 & 0.7596 \\ \cline{2-11}  & sd & 0.1498 & 0.1947 & 0.1544 & 0.2128 & 0.1447 & 0.1797 & 0.1549 & 0.1705 & 0.1897 & 0.1548 & 0.1639 \\ \cline{2-11}  & last & 0.9999 & 1.0000 & 1.0000 & 0.0017 & 0.9998 & 0.9998 & 1.0000 & 1.0000 & 0.9999 & 1.0000 & 0.9860 \\ \hline \multirow{4}{*}{**G**} & min & 0.5000 & 0.0000 & 0.0000 & 0.5000 & 0.0001 & 0.0001 & 0.0000 & 0.0000 & 0.0000 & 0.5000 & 0.0000 \\ \cline{2-11}  & max & 1.0000 & 0.5000 & 0.5000 & 0.9642 & 0.5000 & 0.5000 & 0.5000 & 0.5000 & 0.5000 & 1.0000 & 0.5000 \\ \cline{1-1} \cline{2-11}  & avg & 0.8803 & 0.1386 & 0.1117 & 0.8126 & 0.1103 & 0.1401 & 0.1133 & 0.1284 & 0.1316 & 0.8862 & 0.1278 \\ \cline{1-1} \cline{2-11}  & sd & 0.1837 & 0.2017 & 0.1858 & 0.1747 & 0.1781 & 0.1805 associated with the Question non Answered occurred in different instants of time. Both patients always used the touchscreen (the VoiceInteractionQuality metric ends close to 0.0). The remaining 10 patients have completed the test using the Remote Control device. Patients in group G #7 obtain identical results that the ones in G #3. Although the only difference was the interaction mechanism used, the values obtained for the VoiceInteractionQuality property are identical, since neither used voice interaction. Patients #11 (G #8) and #15 (G #9) also performed the test in a similar way, as they both answered the first question at the second chance. However, Patient #11, before answering, paused the test and then resumed it. If we observe the model (Listing 3), we can see how pausing and resuming the test significantly affects Performance but very little Interaction. This is the reason why worse results are obtained for Performance and practically identical for the Interaction property. Tables 11 and 12 show how patients performed the Get Up & Go tests and the results obtained, respectively. Twelve patients performed the tests properly: they followed the robot instructions and the robot was able to detect all the movements and return a score. In that case, results show how the Performance and the Interaction properties reach almost 1.0, as expected. More details are available in Table 13. Only Patient #4 did not complete the test. The robot only detected the patient standing next to the chair and sat down. Thus, the minimum values for Performance and Interaction remain at 0.5 and the maximum values reach 0.93, although the latest values are lower than those obtained by the other patients.