## 5 Discussion and Future Work  
In 1993, [PERSON] and [PERSON] [45] studied a spherical wrist parallel manipulator which could perform pure orientation in three-dimensional space. They identified that the rotational freedom of each leg of the 3 SPS/S parallel wrist having two spherical pairs at its extremities did not affect the location of the moving platform. However, they performed a case study using a 3 UPS/S manipulator which was obtained by replacing one spherical pair with a universal joint which eliminated the aforementioned rotational freedom. A 3 UPS/S manipulator is used for the first time in an exoskeleton system as a wrist rehabilitation robot in this research, i.e., the 3 UPS manipulator combined with the human wrist and arm constitute the 3 UPS/S architecture of the robot. This is a new approach adopted in this work. The prismatic joints are the active ones of this robot. The top platform of the robot has to be rotated about a fixed centre. In order to achieve the desired motion, the prismatic joints are actuated all together at the same time but in different directions. This approach to rotate the top platform without shifting its centre needs some accurate inverse kinematics solutions. The mechanical architecture of the proposed exoskeleton for wrist mobility rehabilitation is shown in Figure 2. The proposed robot enables a compact robot design that revolves around the human arm. Furthermore, the 3 UPS/S platform's compact design, which revolves around the human arm, enhances wearability and increases the exoskeleton's useful workspace. In addition to the previously mentioned advantages, the device possesses a high structural stiffness. Because this exoskeleton is grounded using a stand, it can accommodate various arm sizes and weights. It can also be used by operators who share the same mean arm dimensions or belong to the same age group. The control of the proposed exoskeleton is achieved by programming an Arduino board with the inverse kinematic solutions, which moves the human hand using linear electric actuators. For our application, simple position control is sufficient and advanced dynamic control is not required. During the working of the system, the top platform performs the desired motion and it means that the system's controller is stable. Thus, in future work, a method for designing the output-feedback optimum control (OFOC) will be developed [46]. Future work will include attaching myoelectric sensors to capture wrist movements. This will improve the robustness and accuracy of the exoskeleton system and will open new applications such as controlling the robot using the active limb. Robots have improved their ability to analyse sensory data, make smart decisions, and carry out tasks precisely and effectively by utilizing machine learning and adaptive learning in sensor fusion. The machine-to-cloud (M2C) layer makes use of cloud computing and storage resources to offer extra capabilities. This makes it possible for robots to access sophisticated machine learning models, large-scale data storage, and data processing algorithms to increase their intelligence and capabilities. In recent years, deep learning has demonstrated outstanding performance. Reinforcement Learning (RL) has demonstrated amazing results in numerous scenarios and superhuman performance in certain difficult robotics tasks by utilizing deep learning [47]. This study of the 3 UPS/S manipulator, which serves as a PW exoskeleton, considers several design factors that impact the robot workspace. These characteristics include the distance of the moving platform in relation to the base, the radii of the moving and base platforms, the ROM of the spherical joints, and the actuator's stroke length. The optimal dimensional design of PM is a fundamental problem in the design of PMs. The main difficulties encountered in the dimensional design of PMs are related to modelling, workspace, kinematics, and control [48]. The dimensional design of the proposed exoskeleton robot will be the subject of the intended future work.