## 2 Materials and Methods
### Force Assessment System Based on Virtual Reality Games  
A Force Assessment System based on VR games was developed to assess the child's improvements in grip force control and modulation. The system was composed of force sensors positioned at the fingertips of the Gloreha Sensor Glove and of custom-designed VR games in the form of tracking tasks purposely developed to assess different aspects of force control and modulation. Previous works in the literature proposed tracking tasks for the assessment and training of grip force control in mildly to severely affected hemiparetic stroke patients. In the study of [PERSON] et al. [22], the authors presented and tested a grip force training system that enabled the improvement of grip force control in 8 out of 10 post-stroke patients. In the study of [PERSON] et al. of 2012 [23], the authors proved that the power grip force tracking tasks developed to assess grip force modulation capability were feasible to quantify the accuracy of grip force control. The force sensors to be embedded in the Gloreha Sensor Glove were chosen according to the following technical specifications: (i) maximum dimension of \(2\times 10^{-2}\) m diameter; (ii) thickness lower than \(5\times 10^{-4}\) m; (iii) force range comparable to the one detected during hand rehabilitation training (0-25 N) [24]. The piezoresistive sensor FSR(r) Model 402 Short Tail (Interlink Electronics) was selected to meet the specifications. It has a diameter of \(1.83\times 10^{-2}\) m, a thickness of \(4\times 10^{-4}\) m, a force sensitivity range of 0.2-20 N and continuous force resolution. Piezoresistive sensors were selected because they are low cost, suitable for wearable applications, require a very simple conditioning electronics and have a good shock resistance. Three sensors were embedded, respectively, in the fingertips of the first, second and third finger of the Gloreha Sensor Glove, i.e., the fingers mostly involved in daily life grasps, as shown in Figure 2. The interface between the sensor and the glove was modified by fixing a thin 3D printed PLA plate with double-sided tape (\(1\times 10^{-3}\) m thickness and \(2\times 10^{2}\) m diameter) to uniformly distribute the force on the sensitive area of the sensor. A 3D-printed PLA support was positioned to interlock the plastic components of the glove that allow connecting Gloreha Sinfonia flexible transmissions to the glove itself. The sensors are secured on the fingertips by means of an elastic band fastened at the top of the PLA support. The sensors with the developed PLA plate were calibrated using the Instron(r) testing machine to relate the force and output voltage. The VR game was developed with Unity, using Microsoft Visual Studio as the pre-set editor and C# as the programming language. Attention was paid to provide an intuitive, clear and engaging visual feedback to the user. In fact, providing the patient with biofeedback can improve the outcome of the treatment and promote neuoplasticity [22]. The aim of the VR game in the form of tracking tasks was to assess the patient capability to finely control the sub-maximal forces exerted when grasping real objects, the ability to balance and release the grip and the general accuracy of force control. The average force exerted by the three fingers was given in input to the VR game to move the avatar according to the force exerted on the object grasped by the participant (i.e., a wood parallelepiped \(1.35\times 10^{-1}\) m \(\times\) 6.5 \(\times\) 10\({}^{-2}\) m \(\times\) 4 \(\times\) 10\({}^{-2}\) m). In the proposed VR game, shown in Figure 3, the patient was asked to move the avatar of the game vertically, according to the exerted force, in order to track the three proposed waveforms moving on the screen. The three waveforms were a \"Ramp\", a \"Square Wave\" and a \"Sinusoidal Wave\" [25].