## 5 Results
### Testing and Validation
\begin{table}
\begin{tabular}{c c c} \hline \hline
**ID** & **Nighttime** & **Daytime** \\ \hline R-BRA01 & 10:41 p.m.–07:59 a.m. & 08:00 a.m.–10:40 p.m. \\ \hline R-BRA02 & 10:01 p.m.–05:59 a.m. & 06:00 a.m.–10:00 p.m. \\ \hline R-BRA03 & 10:01 p.m.–07:59 a.m. & 08:00 a.m.–10:00 p.m. \\ \hline R-BRA04 & 09:16 p.m.–08:59 a.m. & 09:00 a.m.–09:15 p.m. \\ \hline R-BRA05 & 11:59 p.m.–07:34 a.m. & 07:35 a.m.–11:58 p.m. \\ \hline R-BRA06 & 09:51 p.m.–05:29 a.m. & 05:30 a.m.–09:50 p.m. \\ \hline R-BRA07 & 08:51 p.m.–05:59 a.m. & 06:00 a.m.–08:50 p.m. \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Volunteers’ nighttime and daytime windows. Figure 6: Ascent and descent glucose rate from individual R-BRA07 during 14 days along nighttime (from midnight to eight am) considering time intervals of 30 min. For the night-time window, Table 8 details the PEG of each PH (from 15 min to 8 h). It can be depicted that 93.7% of measurements, on average, fall in zones A and B. The same result is presented in Figure 8, showing a total of 1400 predictions. It is important to observe that, for a PH of 480 min (eight hours), the Tesseratus model presented a PEG of 95% falling between zones A and B. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**PH** & **A (\%)** & **B (\%)** & **C (\%)** & **D (\%)** & **E (\%)** & **A + B (\%)** \\ \hline
15 min & 93 & 6.8 & 0.2 & 0 & 0 & 99.8 \\ \hline
30 min & 76.9 & 22.2 & 0.8 & 0 & 0 & 99.1 \\ \hline
60 min & 56.4 & 41.5 & 2 & 0.1 & 0 & 97.9 \\ \hline
90 min & 50.1 & 44.9 & 4.7 & 0.3 & 0 & 95 \\ \hline
120 min & 50.3 & 41.8 & 7.4 & 0.5 & 0 & 92.1 \\ \hline
180 min & 46 & 44 & 8.9 & 0.9 & 0.2 & 90 \\ \hline
240 min & 49.6 & 40.4 & 9.7 & 0.3 & 0 & 90 \\ \hline
**Average** & 62.3 & 32.8 & 4.4 & 0.5 & 0 & **95.1** \\ \hline \end{tabular}
\end{table} 
Table 7: Results of PEG for Tesseratus (3804 predictions plotted)—daytime period. Figure 7: PEG (daytime period) for seven T1D individuals. Green dots lay at zones A and B (95.1% on average): 3804 predictions. Figure 8: Parkes error grid (night period) for seven T1D individuals. Green dots lay at zones A and B (93.7% on average): 1400 predictions. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**PH** & **A (\%)** & **B (\%)** & **C (\%)** & **D (\%)** & **E (\%)** & **A + B (\%)** \\ \hline
15 min & 86 & 12.4 & 1.7 & 0 & 0 & 98.4 \\ \hline
30 min & 72.2 & 26.9 & 0.9 & 0 & 0 & 99.1 \\ \hline
60 min & 57.1 & 41.8 & 1.1 & 0 & 0 & 98.9 \\ \hline
90 min & 50 & 44.4 & 5.6 & 0 & 0 & 94.4 \\ \hline
120 min & 47.7 & 46.7 & 5.6 & 0 & 0 & 94.4 \\ \hline
180 min & 45.3 & 44.7 & 8.6 & 0.7 & 0.6 & 90 \\ \hline
240 min & 48.8 & 42.2 & 8.4 & 0.6 & 0 & 91 \\ \hline
300 min & 46.2 & 44.8 & 8 & 1.2 & 0 & 91 \\ \hline
360 min & 54.2 & 37.8 & 6.5 & 1.5 & 0 & 92 \\ \hline
420 min & 52.3 & 39.7 & 6.7 & 1.3 & 0 & 92 \\ \hline
480 min & 62 & 33 & 4.5 & 0.5 & 0 & 95 \\ \hline
**Average** & 55.8 & 37.9 & 5.6 & 0.7 & 0 & **93.7** \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Results of PEG for Tesseratus (1400 predictions plotted)—night period. Among other well-known error evaluation metrics, such as mean absolute percentage error (MAPE), mean absolute error (MAE) and root mean square error (RMSE), we considered MAE and MAPE the most relevant to evaluate the success of our model, because T1D individuals need predictions as close to real measurements as possible. Thus, the lower the MAE and MAPE values, the better the model is in relation to the prediction. In fact, such metrics are calculated considering absolute values for the difference (measured value minus predicted glucose concentration). Therefore, we evaluate MAE and MAPE considering such errors for all PHs, and organized them for daytime and night-time in Tables 9 and 10, respectively. It is important to note that the daytime window runs from 15 to 240 min and night-time window from 15 to 480 min. there is no literature presenting these prediction horizons. However, we compared Tesseratus with other models that address a shorter PH.