## 3 Results and Discussion
### Testing Candidates
Finally, if the needle of the gauge is in the red zone, it indicates that the person is unhealthy (cardiovascular health-wise) and requires serious attention from specialists. The semi gauge indication tool in Figure 3c produces a reading in the green zone, meaning that the test candidate is, health-wise, in the safe zone. The same computational techniques are employed for the classification of the same individual using the fifth-order PMLD matrix architecture. It can be observed that the variance value produced for this individual places him into the healthy candidates category as seen in Figure 3d. The decision support system performs the interpolation based upon the rules established in Table 5 and shows a zero probability for the individual to be classified as unhealthy as seen in Figure 3e. Finaly, the semi-gauge indication tool also categorizes the individual under the green region as seen in Figure 3f. Both the third and fifth order PMLD matrix configurations identify the individual as a healthy candidate. It is important to emphasize that the individual is known to be healthy, as there have been no previously recorded symptoms of atrial fibrillation episodes. The purpose of this analysis is to add the individuals' cardiac parameters into the entire algorithm and classification technique and to determine if the system is capable of classifying the person as healthy for both the third and fifth order PMLD matrix architectures. Figure 4 shows the ECG parameters of another test candidate. The decision support system for third-order PMLD matrices implies that the person is healthy, as shown in Figure 4a. The probability of the individual being unhealthy is close to zero, as observed in Figure 3b. Furthermore, the semi-gauge indicator tool depicts the individual's health state under the green color (Figure 4c). Again, the same computational routine is performed for  
Figure 3: First test candidate under the classification criteria for the third and fifth order PMLD matrices. the ECG parameters for the fifth-order PMLD matrix. It can be noted that the classification criteria classify the individual under the category of healthy persons (Figure 4d). The decision support system shows a zero probability for the individual being unhealthy as seen in Figure 4e. Similarly, the semi-gauge indication tool also depicts the health status of the person under the green zone (Figure 4f). The increased sensitivity attained with the fifth-order PMLD is obvious when the needle is positioned inside the green zone. Whether using the third or fifth order matrices, the decision support system continually provides engaging conclusions, situating the person within the green zone, which indicates a positive health state. The ECG parameters of the third test candidate undergo evaluation within the classification criteria of both the third- and fifth-order PMLD matrices. As depicted in Figure 5a-c, the individual falls within the classification interval of unhealthy candidates for the third-order PMLD matrix. The developed decision support system shows a large probability for the individual being unhealthy. This classification also aligns with the indication provided by the semi-gauge indication tool, which points towards the red zone. Moreover, the individual's ECG parameters are also tested and subjected to evaluation under the fifth-order PMLD matrix. Again, the developed decision support system classifies the individual as an unhealthy candidate, as evidenced by the semi-gauge indication tool (Figure 5d-f). The utilization of the PMLD matrix architecture emerges as a robust and flexible mathematical tool for effectively analyzing the relationships between the parameters of the ECG signal. Previous studies [12; 13; 14] have already underscored the efficacy of PMLD as a mathematical technique for analyzing ECG signals and their parameters. Figure 4: Second test candidate under the classification criteria for the third and fifth order PMLD matrices.