## 4 Discussion
### Study of Selected Features
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**This Work (LS-SVM RBF)**} & \multicolumn{2}{c}{**SVM RBF**} & \multicolumn{2}{c}{**SVM Quadratic**} & \multicolumn{2}{c}{**NN Class**} \\ \multicolumn{2}{c}{**All Features**} & \multicolumn{2}{c}{**Selected**} & \multicolumn{2}{c}{**All Features**} & \multicolumn{2}{c}{**All Features**} & \multicolumn{2}{c}{**Selected**} & \multicolumn{2}{c}{**All Features**} & \multicolumn{2}{c}{**Selected**} \\ \multicolumn{2}{c}{**Mean \(\pm\) Std**} & \multicolumn{2}{c}{**Mean \(\pm\) Std**} & \multicolumn{2}{c}{**Mean \(\pm\) Std**} & \multicolumn{2}{c}{**Mean \(\pm\) Std**} & \multicolumn{2}{c}{**Mean \(\pm\) Std**} & \multicolumn{2}{c}{**Mean \(\pm\) Std**} & \multicolumn{2}{c}{**Mean \(\pm\) Std**} & \multicolumn{2}{c}{**Mean \(\pm\) Std**} \\ \hline PPV \% & 98.74 \(\pm\) 0.13 & 98.83 \(\pm\) 0.11 & 98.69 \(\pm\) 0.24 & 98.64 \(\  
episodes. In the case of the occurrence of AF, the values of \(\beta_{2}\) and \(\beta_{3}\) could be negative, in contrast to the other parameters used. This behavior was similar to that observed in ref. [33]. Non-AF (or NSR) occurrence was characterized by higher positive values than AF episodes. The EEMD methodology was used for the computation of these parameters. However, this makes these parameters unsuitable for online operation due to the considerable computational complexity [57; 59]. For the remaining parameters of the second group, the values of the features taken into account were not in ranges that could be clearly defined. Compared to parameters such as \(\text{HFD}_{aa}\), SpEn, and HFD, whose range of value variation was very narrow, the variability of values for the rest of the parameters was greater. However, most often, the values that were assigned to the AF class overlapped to some extent with those assigned to the non-AF class. An interesting point of distinction between the classes of atrial fibrillation occurrence and absence was provided by the parameters \(E_{\text{w1}}\) and \(E_{\text{w2}}\), which are defined as the maximum entropy value (Shannon entropy) in individual sub-bands for the high- and low-resonance components of the DQ-TQWT [10]. The DQ-TQWT produced two ratios, \(\zeta_{1}\) and \(\zeta_{2}\), which measured the ratio of maximum energy to average energy for high- and low-resonance components. Table 3 shows that these two parameters, although presenting overlapping value ranges, could be used to differentiate between AF occurrence and non-occurrence cases. The usefulness of this parameter was further demonstrated by its frequent presence in the feature set that yielded the highest accuracy (see Figure 6). In this case, \(\zeta_{1}\) appeared slightly more often than \(\zeta_{2}\). The last group of parameters was calculated from the variance of the MODWT. In this study, nine values of \(\tilde{\phi}_{j}^{2}\) were selected, but not all allowed for an equal contribution to the reduced set of features. The parameters of the most significance were \(\tilde{\phi}_{2}^{2},\tilde{\phi}_{5}^{2},\tilde{\phi}_{3}^{2}\), and \(\tilde{\phi}_{4}^{2}\) (these parameters are listed in descending order of frequency of occurrence in Figure 6). The TPN parameter proved its usefulness in detecting atrial fibrillation. The results of the Mann-Whitney U-test presented in Table 3 show that there were differences in the value distribution of this parameter for AF and normal-beat distribution for the atrial activity segment in the ECG.