## 3 Results
In the case of problems related to blood pressure, for example, management and treatment strategies, such as medication adjustments or lifestyle changes, can be implemented to keep blood pressure levels within healthy ranges. For problems related to chronic diseases such as diabetes or asthma, the IoMT system can help to continuously monitor blood glucose levels or respiratory function, respectively, and provide personalized recommendations for managing these conditions. It is important to note that the IoMT system does not replace professional medical intervention but acts as a complementary tool for the monitoring and early detection of health problems. Medical staff remain responsible for interpreting the data provided by the system, making clinical decisions, and designing individualized treatment plans based on each patient's needs. The mobile application developed for patient registration was programmed in Java, allowing for easy and fast patient data collection. Medical and support staff were trained to use the IoMT system and interpret the collected data. Table 6 evaluates the efficiency of the real-time vital signs monitoring system for 20 patients. The results in the table were obtained through an exhaustive evaluation of the implemented IoMT system. To obtain the values of the different metrics, tests and performance analyzes were carried out using clinical and simulated data sets. The methods used to calculate each of the metrics are described below:  
* Response time (in seconds): Response time refers to the time it takes for the system to respond after receiving a request. In this case, response time measurements were performed during the real-time monitoring of the patient's vital signs, and the times elapsed from the receipt of the data in.csv format until the generation of a complete and updated response was recorded. The average of these response times was calculated to obtain the value of 0.32 s.
* Sensitivity: Sensitivity measures the system's ability to detect positive cases correctly. It is determined by comparing the system results with known actual values. In this case, clinical data sets containing information on the presence or absence of certain medical conditions were used. The system's ability to correctly identify positive issues was evaluated, and a sensitivity value of 0.92 was obtained. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**UserID** & **Age** & **Weight (kg)** & **Height (cm)** & **A 1** & **B 2** & **C 3** & **D 4** \\ \hline
1 & 45 & 62.4 & 162 & Hypertension & 36.8 & 88 & 132/85 \\
2 & 60 & 82.7 & 180 & Diabetes, obesity & 37.1 & 75 & 141/94 \\
3 & 33 & 70.5 & 174 & Asthma, hypertension & 36.6 & 76 & 123/79 \\
4 & 42 & 54.2 & 157 & Anemia, hypothyroidism & 36.9 & 92 & 115/70 \\
5 & 50 & 68.9 & 175 & Hypertension, dyslipidemia & 37.2 & 80 & 127/83 \\
6 & 28 & 60.1 & 163 & No previous illnesses & 36.7 & 84 & 120/80 \\
7 & 67 & 75.2 & 178 & Hypertension, dyslipidemia & 36.9 & 72 & 137/90 \\
8 & 55 & 64.3 & 159 & Hypertension, diabetes & 37.1 & 88 & 128/84 \\
9 & 47 & 79.1 & 182 & Asthma, hypertension, and dyslipidemia & 36.7 & 74 & 124/82 \\
10 & 38 & 56.8 & 166 & No previous illnesses & 37 & 96 & 120/78 \\
11 & 52 & 73.5 & 177 & Hypertension, dyslipidemia & 36.8 & 78 & 129/85 \\
12 & 30 & 62.1 & 168 & No previous illnesses & 37.3 & 82 & 118/76 \\
13 & 65 & 80 & 181 & Diabetes, hypertension & 36.6 & 70 & 138/91 \\
14 & 43 & 61.5 & 160 & Asthma & 36.9 & 90 & 119/77 \\
15 & 27 & 73.2 & 179 & Obesityad, hypertension & 37 & 72 & 125/80 \\
16 & 51 & 67.8 & 165 & Diabetes & 37.1 & 89 & 130/85 \\
17 & 57 & 76.5 & 181 & Dyslipidemia & 36.8 & 75 & 128/83 \\
18 & 39 & 58.6 & 162 & No previous illnesses & 36.6 & 83 & 115/75 \\
19 & 46 & 84.3 & 179 & Hypertension & 37.3 & 80 & 137/90 \\
20 & 32 & 63.9 & 167 & Asthma & 36.7 & 87 & 120/80 \\ \hline \hline \end{tabular}  
* A \({}^{1}\) = Previous illnesses; B \({}^{2}\) = Basal heart rate (beats per minute); C \({}^{3}\) = Basal body temperature (\({}^{\circ}\)C); D \({}^{4}\) = Basal blood pressure (mmHg).  
\end{table}