## 2 Materials and Methods
### The Robotic Device Set's Identification  
In the first step of the study, a multidisciplinary team worked to identify a set of technological and robotic devices to treat the upper limb globally. The team was created in April 2015, at our institution (Fondazione Don Carlo Gnocchi, FDG) consisting of the medical director of FDG, 3 physiatrists, 2 neurologists, 3 physiotherapists, and 4 bioengineering, coordinated by the head of the Innovation and Health Technology Assessment department. The team, created with the intent of developing a strategy for the implementation of robotic rehabilitation within the FDG centers, performed an analysis  
Figure 1: Steps of the study. First step: a multidisciplinary team identified a set of technological and robotic devices to treat the upper limb. Second step: 30 stroke patients were enrolled and treated either with the identified set of four devices (16 patients), or with a conventional treatment (14 patients). of robotic solutions commercially available, to generate a prioritized list of solutions of potential interest for acquisition by the FDG. The team also had the objective of following the deployment of the robotic solutions in the various centers of our institution and promoting the use of such solutions. The group, involving five different centers of the FDG throughout Italy, assessed different devices. A consensus building process was used to create a specific form aimed at standardizing the description of the devices and allowing for an easier comparison between them (see the supporting document: FDG Robotic System Characteristics Form). The analyzed features included general information (commercial name, manufacturer, distributor, name of the compiler, and confidence level of the compiler), system characteristics (type of system, treated body segment, stage of development, type of movement, portability, type of assistance provided by the system, main control inputs, configurability, normative values, and outcome measures), the possibility for patients to use it with a wheelchair, safety issues, literature data, costs of purchase and maintenance, an indication of the purchasing priority (by motivations), and efficiency parameters (autonomous use by the patient, preparation time, possibility of using the solution in group therapies, and number of clinicians involved during treatment). These features were selected according to the clinical and rehabilitative needs; organizational aspects as well. The team evaluated 10 different devices by filling out 40 forms (the same solution was evaluated by several people in the team). The evaluated solutions included two exoskeletons, four end-effector systems, two unweighting systems for the upper limb (one electromechanical and one spring based) and two sensorized technological systems (Table 1). All the data were collected and the \"qualitative\" texting scales of the forms were transformed into \"quantitative\" ones (Table 2). Then, the last three parameters were combined to evaluate the efficiency level (Equation (1)):  
\[Efficiency\;level=\frac{Autonomous\;use\times Group\;therapy}{Number\;of\; clinicians\;involved} \tag{1}\]  
The efficiency level is an index representing the potential resource optimization, in terms of cost reduction, that could be obtained by using the robotic solution. In Equation (1) the efficiency level increases when the robotic solution can be used by the patient autonomously and if it is suitable for group therapies, while it becomes lower if it requires constant control by a physiotherapist. Similarly, the number of clinicians involved in the treatment also influence the efficiency level: if more than 1 clinician is needed to let the patient use robotic solution, the efficiency level decreases.