## 3 Results
### WOB Level Classification
\begin{table}
\begin{tabular}{c c c c c c c} \hline \multirow{2}{*}{**Parameter/Index**} & \multicolumn{3}{c}{_Restrictive (E\({}_{1}\))_} & \multicolumn{3}{c}{**P-Value**} \\ \cline{2-7}  & **G\({}_{1}\)** & **G\({}_{2}\)** & **G\({}_{3}\)** & **G\({}_{1^{*}}\)G\({}_{2}\)** & **G\({}_{1^{*}}\)G\({}_{3}\)** & **G\({}_{2^{*}}\)G\({}_{3}\)** \\ \hline
**WOB\({}_{\text{r}}\) (J/L)** & 0.61 \(\pm\) 0.13 & 1.02 \(\pm\) 0.14 & 1.52 \(\pm\) 0.13 & \(<\)0.05 & \(<\)0.05 & \(<\)0.05 \\ \hline
**MaxAmpDia (mV)** & 0.024 & 0.032 & 0.054 & * & \(<\)0.05 & \(<\)0.05 \\
[0.022–0.030] & [0.022–0.049] & [0.040–0.068] & & & \\ \hline
**MaxAmpInt (mV)** & 0.020 & 0.032 & 0.034 & & \\
[0.016–0.027] & [0.020–0.043] & [0.020–0.049] & \(<\)0.05 & \(<\)0.05 & * \\ \hline
**MaxAmpStrn (mV)** & 0.018 & 0.021 & 0.021 & * & * & * \\  & [0.010–0.024] & [0.014–0.036] & [0.017–0.041] & & & \\ \hline
**C\({}_{\text{Dia\text{-}Int}}\)** & 0.66 [0.62–0.68] & 0.67 [0.65–0.75] & 0.71 [0.67–0.83] & * & \(<\)0.05 & * \\ \hline \(\alpha_{1}\) & 0.55 \(\pm\) 10-5 & 1.07 \(\pm\) 0.04 & 1.55 \(\pm\) 10–5 & - & - & - \\ \hline \(\alpha_{2}\) & 0.45 \(\pm\) 10-5 & 0.93 \(\pm\) 0.04 & 1.45 \(\pm\) 10–5 & - & - & - \\ \hline \multicolumn{7}{c}{**Obstructive (E\({}_{2}\))**} \\ \hline
**WOB\({}_{\text{r}}\) (J/L)** & 0.63 \(\pm\) 0.12 & 1.03 \(\pm\) 0.14 & 1.51 \(\pm\) 0.12 & \(<\)0.05 & \(<\)0.05 & \(<\)0.05 \\ \hline
**MaxAmpDia (mV)** & 0.028 & 0.031 & 0.050 & * & \(<\)0.05 & \(<\)0.05 \\
[0.021–0.038] & [0.023–0.047] & [0.038–0.083] & & & \\ \hline
**MaxAmpInt (mV)** & 0.016 & 0.019 & 0.023 & * & * & * \\  & [0.010–0.029] & [0.013–0.036] & [0.015–0.045] & & & \\ \hline
**MaxAmpStrn (mV)** & 0.016 & 0.017 & 0.030 & * & \(<\)0.05 & \(<\)0.05 \\
[0.010–0.023] & [0.013–0.022] & [0.019–0.048] & & & \\ \hline
**C\({}_{\text{Dia\text{-}Int}}\)** & 0.79 [0.75–0.84] & 0.75 [0.72–0.78] & 0.73 [0.69–0.75] & \(<\)0.05 & \(<\)0.05 & * \\ \hline \(\alpha_{1}\) & 0.55 \(\pm\) 10–5 & 1.05 \(\pm\) 10–5 & 1.55 \(\pm\) 10–5 & - & - & - \\ \hline \(\alpha_{2}\) & 0.45 \(\pm\) 10–5 & 0.95 \(\pm\) 10–5 & 1.45 \(\pm\) 10–5 & - & - & - \\ \hline \end{tabular}  
* There are no statistically significant differences between groups.  
\end{table} 
Table 4: Median and standard deviation of real work of breathing values for each group. G1: Low WOB; G2: medium-high WOB; G3: elevated WOB. Furthermore, the parameters of each model and the selected index values for classification model are shown. third quadrant, there is the NN model, where the loss function of both datasets can be considered low. Therefore, this NN was selected. The neural network selected for the final model (see Figure 4 and Table 5) obtained an accuracy of 89%, a specificity of 83.67%, a sensitivity of 96.36% (group 2 and group 3), a sensitivity of 90.12% (group 2), and a sensitivity of 89.66% (group 3) (see Table 6). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{4}{c}{**Real Values**} \\ \cline{2-6}  & & **Group 1** & **Group 2** & **Group 3** & **Total** \\ \hline \multirow{4}{*}{**Predicted Values**} & **Group 1** & 41 & 4 & 0 & 45 \\ \cline{2-6}  & **Group 2** & 5 & 73 & 3 & 81 \\ \cline{2-6}  & **Group 3** & 3 & 4 & 26 & 33 \\ \cline{2-6}  & **Total** & 49 & 81 & 29 & 159 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Confusion matrix for the final classification model of Figure 4.