## 5 Experimental Results and Contributions
### Real Environment Validation  
To validate the system in a real environment, a test was carried out with five rehabilitation patients who used the system for over a month. The study was carried out thanks  
Figure 8: Monitoring interface. Figure 9: Information graphics. to the collaboration with a clinic specialized in physical rehabilitation. All the patients voluntarily agreed to carry out the test and were duly informed. This process involving human subjects in the tests was carried out in accordance with the Helsinki Declaration of 1964, Ethical Principles for Medical Research Involving Human Subjects. The volunteers (two men between 23 and 52 years old, together with three women between 26 and 47 years old) were undergoing a rehabilitation process due to muscular pain in the performance of certain daily movements. The experiment was carried out for over a month, with an initial session and four control sessions over the month, corresponding to one session per week. The exercises performed were designed to eliminate certain causes of pain through preventing certain muscles from becoming atrophied. These exercises were included in the system by an expert in sports under the supervision of a specialized doctor, confirming that these exercises were performed properly and would help the patient. Throughout the month, users did the different exercises established by the doctor to improve their condition. In each of the sessions, the different parameters collected by the system were analyzed, such as the angle of the movements, pulses per minute, and the level of oxygen in the blood. In Figure 10, the patient can be seen with the VR equipment. In this case, the VR system was used to carry out the experiments so that their operation and the level of satisfaction with the patient could be monitored. In Figure 11, the patient can be seen performing an exercise with the VR system. Figure 10: User with Oculus and Enflux suit. To verify that the system correctly detected the errors made by the patient, a face-to-face control of the user was carried out in the first session. During this control, each of the patients was asked to perform each of the established exercises with the system components on. In addition, a recording was made from different angles of the patient. The sports expert was then asked to visually identify the number of errors made by the patient. Once the exercise was completed, the number of errors detected by the system in the execution of the exercise was collected to compare its effectiveness in detecting these errors. The results obtained can be shown in Table 2.  
Table 2 indicates that the system was able to detect more errors than the expert user in real time. To confirm that these errors were real, the expert user was made to review the images captured during the exercise by the patient, verifying that the number was correct and not due to a malfunction of the system. In this way, the effectiveness of the system in this process of detecting bad posture was confirmed. Subsequently, during the four remaining sessions, a process of information gathering was carried out so that it could be verified that the patient was capable of improving his or her way of performing the exercise by reducing the number of errors made in the performance of each of the exercises. These sessions were carried out on Days 7, 14, 21, and 28 of the treatment. The information collected corresponds to the average number of errors made by users during the performance of these exercises during these control sessions. This information can be confirmed in Figure 12. In this image, it can be seen that the patients managed to reduce the errors committed during the execution of these exercises in a logarithmic manner, and that the rapid learning and assimilation process by