## 2 Background  
The last decade has seen a slow increase in telemedicine applications [16]. Within this field, several works have been carried out in areas such as patient activity monitoring systems [17] or systems for the recovery of chronic disease patients [18]. Works that deal with rehabilitating patients remotely, different kinds of data are recorded to monitor them. On remote rehabilitation projects, this data is usually recording with an IoT paradigm [19; 20]. Among the works that make use of this paradigm, [PERSON] et al. [21] analyzed user gait and mobility to give them certain strategies when performing outdoor exercise. The system makes use of Near Field Communication (NFC) technology to obtain the information that is later analyzed. On the other hand, [PERSON] et al. [22] carried out an analysis of different NoSQL databases to determine which is better suited to be used in IOT-based telemedicinesystems. In this case, they highlighted the performance of the MongoDB database in the Cloud for handling this information. Among IoT systems, there are those dedicated to monitoring movements made by different parts of the body to check that movements are carried out properly. These works are focused on the development and use of the so-called exoskeletons [23; 24]. [PERSON] et al. [25] developed a system based on an exoskeleton for the rehabilitation of the ankle. To this end, they constructed an exoskeleton to treat the multiple phases of treatment and shorten the patient's recovery time. On the other hand, [PERSON] et al. [26] developed an ankle exoskeleton to direct three rotation movements through a simple and reliable structure, managing to implement a control system capable of accurately positioning the ankle according to the exercise being performed. From another point of view, there are solutions capable of monitoring whole-body movements of the users. These solutions make use of Deep Learning algorithms for the detection of postures through image processing techniques [27; 28; 29]. [PERSON] et al. [30] developed a motion capture system capable of measuring the kinematics of spacesuits in an underwater test environment. However, these solutions are not 100% effective, which can result in erroneous data that can lead to errors in reviewing patient progress. On the other hand, the development and usage of motion capture suits to capture this information is an active area of research. [PERSON] [31] used the Rokoko motion-capture suit to identify different strategies that could be used to capture the movements of dancers. These movements are later used in film production, editing, and special effects. Another important point of these telerehabilitation systems is user feedback. This feedback makes the user feel more integrated and motivated while showing them their actions. Accessibility, ease of use, and human-computer interactions are also very important aspects. To achieve this, most of the systems developed make use of VR technology. Some studies demonstrate the advantages of using this technology. [PERSON] [32] showed that users performing motor function-related tasks improve its performance after training when obtaining visual feedback. The research group of the authors of this study, the ESALab research group, has previous experience related to VR and rehabilitation systems. [PERSON] et al. [33] proposed an immersive VR rehabilitation system based on the repetition of certain exercises with the help of a exoskeleton. [PERSON] et al. [34] included VR technology to allow a patient with motor difficulties to perform exercises in a very interactive and non-intrusive way, using a set of devices that can be worn, thus contributing to his or her motivational rehabilitation process. In telerehabilitation dedicated projects, the communication and coordination between patients and healthcare members are crucial. Healthcare professionals have to plan exercises and, at the same time, check progress during the rehabilitation process.