# Multi platform Computer Vision System to Support Physical Fitness Assessments in Schoolchildren
## 2 Materials and Methods
### Multiplatform Implementation
#### 2.3.4 Modeling
In the case of the abdominal test, the vectors considered are the vector \"A\", formed between the central point of the chest and the pelvis in the extension phase, while the vector \"A\" is the representation of the same vector in motion. Furthermore, vector \"B\" comprises the pelvis and one of the knees. The vector is shaped with the knee closest to the camera to provide the best possible confidence in joint identification. In the case of the bicep's flexion test, the vector considered is the vector \"C\" formed by the elbow joint with the wrist in the extension phase. In contrast, the vector \"C\" represents the movement of the same vector, in addition to the \"D\" vector formed by the shoulder joint with the elbow. It is essential to mention that, during the execution of both tests, the student's body will begin to generate different angles that are evaluated during the flexion and extension phase, verifying that these angles at some point meet the criterion of being less than a minimum angle and more significant than a maximum angle, defined respectively for each phase, and which are evaluated sequentially in each repetition validating that both angles are reached to consider a correct repetition. In the case of the sit-up test, the minimum angle generated by the vectors \"B\" and \"A\" is equal to 70\({}^{\circ}\), while the maximum angle caused by the vectors \"B\" and \"A\" is equal to 120\({}^{\circ}\). On the other hand, for the bicep's curl test, the minimum angle generated by the vectors \"D\" and \"C\" is equal to 40\({}^{\circ}\), while the maximum angle caused by the vectors \"D\" and \"C\" is equal to 160\({}^{\circ}\). A vector representation of these movements can be seen in Figures 4 and 5. The mobile app was developed in Unity because this version proved to be the most stable when exported to the Android operating system and compatible with the body tracking libraries used. Visual Studio 2022 was used as the code editor. Additionally, the LightBuzz library was imported in its version \"5.5.0\" to allow the recognition of joints and the evaluation of tests with the algorithms. The data architecture is managed using the Firebase real-time database. Mainly, this class will store the anthropometric data of the student, that is, his age, sex, height, weight, waist circumference, body mass index (BMI), and description. It also stores the data of the tests performed: the distance jumped by the horizontal jump and the minimum hip, knee, and ankle angles before the jump, the maximum stretched distance and the hip angle now of maximum stretch, the number of repetitions of sit-ups performed, and the number of biceps curls fulfilled. These are the data of interest for the analysis of motor capabilities. The initial and execution test interfaces of the mobile app are shown in Figures 10 and 11. The types of tests implemented are unit, integral, and functional tests. These types of tests were chosen since they are practical and allow the optimal functioning of the prototype to be verified both in single \"scripts\" and in general. Figure 8: Example of horizontal jump test evaluation without impulse. Figure 9: Flexibility bending test evaluation example. All the tests we will see below, as well as the validation of the prototype, were carried out on a \"Xiaomi 11 Lite 5G NE (Beijing, China)\" cell phone with an Octa-Core 2.4 GHz processor, 8 MB of RAM, and Android 13 + MIUI 14.0.6. Additionally, a validation was carried out with the end user, which was qualified and evaluated. User Experience tests are conducted using interview and survey techniques to determine the user's perception of the developed mobile application. After presenting a user manual to the teachers, which includes the functionalities that the application should satisfy, they were asked to give their opinion on the use of the application. As seen in [PERSON] and [PERSON] [21], they mention that with five users, 90% of the problems can be discovered when carrying out user experience tests.