## 3 Results
### Analysis of the Impact of Physical Activity on CGM Devices' Performance  
1.1 Analysis of the Impact of Physical Activity on CGM Devices' Performance in Different Glucose Ranges  
Figure 2 shows the deviation metrics MAD and MARD for both Eversense and FSL devices by considering different glucose ranges (hypoglycemia, euglycemia, hyperglycemia) and for PA and NDA, respectively. Both MAD and MARD were calculated between pairs of glucose values recorded for each CGM device and capillary glucose measurements (FSLCstrip). In general, both devices showed significantly higher deviations in PA in all glucose ranges. However, Eversense in the hypoglycemic range seems to perform better in PA than NDA, showing smaller MAD and MARD values. For both Eversense and FSL, comparing the glucose ranges, MAD values are the highest in the hyperglycemic range, and for MARD, it occurs for hypoglycemia. It is worth noting that standard deviations (represented by a line in the center of bars) are also high in hyperglycemia (MAD) and hypoglycemia (MARD). This suggested that CGM devices are more sensitive to these glucose ranges, with less accurate glucose measurements compared to FSLcstrip. To evaluate the quality of the glucose measures, we also studied the CEG. The higher concentration of points placed in zone A of the CEG plot, the greater performance of CGM devices. Figure 3 shows the proportion of values in zone A of CEG for both CGM devices during NDA and PA when considering hypoglycemic, euglycemic, and hypergly ranges. In Figure 3, it is observed that Eversense presents a high proportion of measures in zone A (88.5%) during PA when considering the hypoglycemic range. However, the proportions of points in zone A for the PA period are lower than the NDA in the other ranges: 66.4% versus 79.6% (euglycemic range) and 75.9% versus 86.2% (hyperglycemic range). According to the two-proportion test, all differences are statistically significant (represented by *) except for the hypoglycemic range. For FSL (see Figure 3), the scenario is  
Figure 2: MAD and MARD values during PA and NDA for different glycemic ranges for (**a**,**b**) Eversense against FSLCstrip and (**c**,**d**) FSL against FSLCstrip. MAD and MARD were calculated based on the differences between glucose values recorded by the CGM device and FSLCstrip for PA and NDA, respectively. The comparison highlights whether there are significant differences between the PA and NDA conditions across glucose ranges. * indicates statistically significant differences in the impact of physical activity according to the two-proportion z-test (with level of significance of 0.05). different. The proportion of points in zone A for NDA is greater than those obtained in the PA period in all glucose ranges. The differences in proportions are statistically significant in all cases by considering the two-proportion test. Note that the highest proportion in zone A occurs in the hyperglycemic range (92%). In Eversense, the differences in proportions between PA and NDA are smaller compared to values of FSL. This suggests that glucose measurements from Eversense are more accurate, performing better than FSL. 1.2 Analysis of the Impact of Physical Activity on CGM Devices' Performance at Different Time Intervals Throughout the Day  
To study the performance of CGM devices (Eversense and FSL) during the PA and NDA in different time intervals (\(M_{int}\), \(A_{int}\), \(E_{int}\), \(N_{int}\)), the deviation metrics and the CEG were considered. Figure 4 shows the MAD and MARD values for different time intervals by distinguishing between the periods PA and NDA. In Figure 3(a,b), it is observed that there exist differences between PA and NDA for Eversense, with greater MAD and MARD values during the PA period, except for \(N_{int}\). The MAD and MARD values differ significantly during \(M_{int}\) and \(A_{int}\) for both Eversense and FSL in PA and NDA (see Figure 3(a)-d).