## 4 Discussion  
In this work, we studied the performance of CGM devices (Eversense and FSL) compared to the capillary glucose device (FSLCstrip) during periods of high-intensity PA and NDA, when considering (i) three different glucose ranges (hypoglycemia, euglycemia, and hyperglycemia), and (ii) four time periods throughout the day (morning, afternoon, evening, and night). CGM devices have increased their popularity for tracking and controlling glycemic levels because they are less invasive compared to capillary BG measurements that require frequent punctures for obtaining blood samples. Despite these characteristics, in several studies CGM devices have been shown to be less accurate than traditional capillary glucose devices. It is for this reason that the evaluation of CGM performance against gold standard measures becomes crucial to guarantee reliability and confidence in their use, and more particularly during PA. The comparison of the performance of Eversense and FSL against FSLCstrip was performed following two different approaches. Firstly, we analyzed MAD and MARD with respect to the FSLCStrip. Secondly, we visually analyzed how glucose concentrations values are distributed in different zones of CEG plots. We can conclude that these CGM devices present a clinically meaningful deviation compared to FSLCstrip based on MAD/MARD and on the proportion of  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**ML Method** & **Interval** & **Accuracy** & **Sensitivity** & **Specificity** & **F1-Score** \\ \hline \multirow{4}{*}{KNN} & \(F_{int}\) & 0.80 \(\pm\) 0.08 & 0.85 \(\pm\) 0.15 & 0.76 \(\pm\) 0.10 & 0.80 \(\pm\) 0.09 \\  &  
values in zone A, both providing a worse performance whenever the subjects perform PA. This is an important insight to consider, since diabetic patients need strict control of their glucose levels and performing strenuous PA can lead to less accurate glucose measurements when using such type of sensors. Also, when comparing the values of both periods (NDA and PA), it was observed that the distributions of glucose values were significantly different for Eversense and FSL (both in the total and the hyperglyic ranges of glucose), whereas this was not the case for FSLCstrip. These experimental results prove that FSL and Eversense are less accurate for measuring glucose under high-intensity PA scenarios which is in line with previous studies. Moreover, the fact that the differences appear in the hyperglyic range is remarkable since it implies that the sensors work inappropriately when trying to detect glycemic events. This can be critical for T1D subjects because prolonged periods of hyperglycemia are one of the underlying causes of complications related to diabetes. The rapid change in glucose levels during PA continues to be a challenging situation and it is also expected to affect the performance of sensor systems. To extend this work, we studied glucose levels during four different time intervals (\(M_{int}\), \(A_{int}\), \(E_{int}\), \(N_{int}\)) throughout the day. No significant differences were observed among the distributions of each time interval in the NDA period, with stable glucose concentration values during the day. The opposite occurred during the PA period, obtaining significant differences between morning and afternoon, as well as between morning and evening. In a similar way to this previous analysis, the frequency of onset of glucose outside the target range (between 70 and 180 mg/dL) was studied, in particular for hypoglycemic and hyperglyic episodes. Hypoglycemic events appeared to be stable at both periods (PA and NDA). However, hyperglyic events vary significantly at different time intervals during the PA period compared to the NDA period. This makes sense considering that it is known that performing exercise diminishes the glucose storage of the body, therefore avoiding hyperglycemia.