## 4 Discussion
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline  & \(\beta\) & \begin{tabular}{c} **Standard** \\ **Error** \\ \end{tabular} & \(p\) & \
\begin{tabular}{c} **Exp (\(\beta\))** \\ **Relative Risk** \\ \end{tabular} &
\begin{tabular}{c} **95\% Confidence Interval for Exp (\(\beta\))** \\ **Lower Bound** \\ \end{tabular} \\ \hline BI & 0.099259 & 0.039318 & **0.01** & 1.1044 & 1.0224 & 1.1928 \\ DI & \(-\)0.52213 & 0.37 & 0.16 & 0.5933 & 0.2873 & 1.2252 \\ CIRS-SI & \(-\)1.41553 & 0.75418 & 0.06 & 0.2428 & 0.0554 & 1.0647 \\ \hline \multicolumn{6}{l}{Values in bold indicate statistical significance (\(p<0.05\)). BI: Barthel Index; DI: Deambulation Index; CIRS-SI:} \\ \multicolumn{6}{l}{Cityulative Illness Rating Scale-Severity Index.} \\ \end{tabular}
\end{table} 
Table 5: Logistic regression model for the identification of the best physiotherapist/patient ratio (R2/R3 versus R4), considering the mean disability, mobility, and comorbidity of the group (identified in the univariate analysis). Data were obtained from 255 rehabilitation sessions (782 observations). day with a mean value of physiotherapist/patient ratio of 1/3.1, which means eight rehabilitation sessions/day. In a traditional rehabilitation model (with a physiotherapist/patient ratio of 1/1) to treat 24 patients/day, obviously 24 rehabilitation sessions/day are needed. As highlighted in the proposed organizational model, it is possible to reduce the number of rehabilitation sessions/day (needed to treat the same number of patients) by about 1/3, with better human resources allocation. Moreover, it is worthy to note that we have specifically chosen a set of devices with a limited time required to start the rehabilitation session, as highlighted by the reported tSetup, and therefore, these have a limited impact on the provided rehabilitation dose. On the contrary, more complex devices, as exoskeletons, require a longer time to fit the robot for individual patients, and it is one of the main barriers to efficient use [26]. As in our approach, two studies on the same topic [8; 9] used both robotic and non-robotic devices, supporting the idea that this approach can be effective and sustainable. Anyway, robotic rehabilitation is not merely a matter of increasing the amount and intensity of therapy [27]. It provides extrinsic biofeedback that makes the patient aware of his movements and consequently allows him to modify his movement patterns, thus fostering his participation in the rehabilitation exercise [28; 29; 30]. Furthermore, it seems that the impact of technological rehabilitation on functional outcome could be optimized by offering more chances to the nervous system to experience \"real\" activity-related sensorimotor input during the training of upper limb movement [31]. From this knowledge and from our experience, it is very important to underline that physiotherapists have to perform an adequate training to acquire expertise with regard to these devices. With a correct use of them, the workload of the physiotherapists can be alleviated, their work time can be optimized, and they can focused toward personalizing rehabilitation treatments, according to each patient's residual abilities and progress in order to optimize functional recovery [27]. The organizational model herein discussed shows the feasibility of providing a comprehensive and a high technological level upper limb treatment that would be accessible to a high number of patients at once, while preserving an adequate training time and physiotherapist supervision. Finally, thanks to the sustainability in terms of optimizing human resources, this model can be applied to the usual care of the clinical practice considering the advantages that the robotic devices can provide (for example, to objectively measure the improvement during the therapy) [32; 33].