## 4 Discussion  
At baseline, the working volume significantly correlated only with the MAS total score, revealing that spasticity is the main factor that could reduce the volume of movements selected for working with the robots. Although this correlation could be expected because the volume was computed on passive ROMs, the fact that spasticity was the only factor affecting this volume was quite unexpected, as this parameter was neither influenced by pain nor by residual mobility. This result may support the purpose of administering specific treatments for spasticity before the beginning of robotic therapy. This approach was tested in a recent case report of a patient with chronic stroke treated with Armeo(r) Power after Botulinum (BoNT-A) injection [21]. The patient obtained a favorable outcome in terms of upper limb functional recovery [21]. In terms of kinematics, the working volume correlated with all the ranges of shoulder movement around the three anatomical axes, and with the flexo-extension of the elbow, as expected. From a kinetic point of view, the working volume was inversely correlated with the weight support at T1. However, our results showed an important difference between these two parameters: if the working volume was mainly related just to spasticity, the weight support correlated with MRS, VAS, MAS and NIH-SS scores, and a trend was observed even with the BI score, suggesting that this parameter was set by the therapist reflecting the entire clinical condition of the patients. After two weeks of treatment, a general, statistically significant improvement was observed in the patients in terms of increment in working volume and upper limb functions, as well as of decrement in needed weight support, spasticity, pain, and neurological deficits. The intervention was only two weeks, with ten sessions of treatment--while intensive, it is a short period to provide a clear conclusion about the clinical stability of these results, and further studies are needed including follow-up observations for assessing the long-term efficacy of short, intensive robotic therapies. However, it is important to highlight that neuroplasticity can be elicited also in chronic stages of stroke by a short, intensive intervention based on robotic mobilization of the upper limb kinematic chain combined with exergames, providing proprioceptive and visual feedback. Despite these general improvements, the percentage changes in robotic parameters did not correlate with those of clinical scores. Only the improvements in forearm prono-supination were found correlated with the improvements in the FMA-UE score, but also the change in this ROM referred to few degrees. Two weeks of robotic rehabilitation likely induced some changes, but not enough and not for all the patients to show clear correlations among the clinical status of heterogeneous patients and very specific biomechanical parameters of the robot. It limited the possibility of using the parameters used by the robot to assess the rehabilitation outcome, despite providing interesting information about the adaptation that occurred during therapy. The relationship between working volume and spasticity shown in Figure 2 is meaningful. The working volume was significantly correlated with total MAS score both at T1 and T2. Furthermore, a clinical improvement was observed for both parameters, with spasticity significantly reduced in T2 by about 20% despite a high variability among subjects, and working volume increased by about 45% on average. However, their percentage changes were not significantly correlated. These results highlight a clinical meaning of the