# Diagnosing Various Severity Levels of Congestive Heart Failure Based on Long-Term HRV Signal
## 3 Methods
### Validation  
#### 4.2.1 Model A  
Table 8 shows the leave-one-subject-out validation performance of model A for different classification algorithms. The highest accuracy of 97.35% was achieved by using both SVM and KNN (\(K\) = 1) classifiers. However, the SVM used fewer features (number of features (NF) = 5) to achieve the same accuracy of KNN (\(K\) = 1). In order to better apply model A to the clinical diagnosis of CHF disease, we tried our best to make CHF patients not misdiagnosed as normal subjects. Therefore, with the same accuracies of SVM and KNN (\(K\) = 1), the sensitivity indicator was an important index. For the sensitivity and AUC indicators, the performance of the SVM was (Sensitivity = 97.56% and AUC = 0.963) better than the performance of KNN (\(K\) = 1, Sensitivity = 95.12%, and AUC = 0.959). Therefore, considering the better NF, sensitivity, accuracy, and AUC, our work used the SVM classifier to build model A. \begin{table}
\begin{tabular}{l l l l l l l l l} \hline \hline \multirow{2}{*}{**Tolerance**} & \multirow{2}{*}{**Group**} & \multicolumn{2}{l}{**Embedding Dimension**} & \multicolumn{2}{l}{**SampEn**} & \multicolumn{2}{l}{**Embedding Dimension FuzzyMEn**} \\ \cline{3-10}  & & \(m\) = 1 & \(m\) = 2 & \(m\) = 3 & \(m\) = 1 & \(m\) = 2 & \(m\) = 3 \\ \hline \multirow{5}{*}{_r_ = 0.10} & CHF I & 1.12 \(\pm\) 0.11 & 0.96 \(\pm\) 0.10 & 0.85 \(\pm\) 0.08 & 0.81 \(\pm\)0.04 & 0.96 \(\pm\) 0.06 & 0.73 \(\pm\) 0.05 \\  & CHF II & 1.52 \(\pm\) 0.08 & 1.37 \(\pm\) 0.12 & 1.31 \(\pm\) 0.13 & 1.26 \(\pm\) 0.03 & 1.31 \(\pm\) 0.06 & 0.99 \(\pm\) 0.05 \\  & CHF III & 1.69 \(\pm\) 0.10 & 1.55 \(\pm\) 0.13 & 1.47 \(\pm\) 0.14 & 1.27 \(\pm\) 0.11 & 1.36 \(\pm\) 0.11 & 1.04 \(\pm\) 0.08 \\  & CHF IV & 1.94 \(\pm\) 0.15 & 1.78 \(\pm\) 0.16 & 1.68 \(\pm\) 0.16 & 1.38 \(\pm\) 0.20 & 1.48 \(\pm\) 0.15 & 1.08 \(\pm\) 0.07 \\  & \(p\)-value & 8 \(\times\) 10\({}^{-4}\) ** & 2 \(\times\) 10\({}^{-3}\) ** & 2 \(\times\) 10\({}^{-3}\) ** & 0.05 \({}^{*}\) & 0.12 & 0.13 \\ \hline \multirow{5}{*}{_r_ = 0.15} & CHF I & 0.96 \(\pm\) 0.05 & 0.80 \(\pm\) 0.05 & 0.70 \(\pm\) 0.04 & 0.87 \(\pm\) 0.02 & 0.67 \(\pm\) 0.05 & 0.51 \(\pm\) 0.03 \\  & CHF II & 1.48 \(\pm\) 0.06 & 1.33 \(\pm\) 0.08 & 1.27 \(\pm\) 0.10 & 1.02 \(\pm\) 0.07 & 1.07 \(\pm\) 0.04 & 0.82 \(\pm\) 0.05 \\  & CHF III & 1.41 \(\pm\) 0.19 & 1.27 \(\pm\) 0.20 & 1.19 \(\pm\) 0.18 & 0.99 \(\pm\) 0.13 & 1.10 \(\pm\) 0.14 & 0.81 \(\pm\) 0.07 \\  & CHF IV & 1.59 \(\pm\) 0.21 & 1.39 \(\pm\) 0.25 & 1.30 \(\pm\) 0.23 & 1.04 \(\pm\) 0.18 & 1.15 \(\pm\) 0.15 & 0.82 \(\pm\) 0.06 \\  & \(p\)-value & 0.06 & 0.13 & 0.10 & 0.10 & 0.09 & 0.13 \\ \hline \multirow{5}{*}{_r_ = 0.20} & CHF I & 0.68 \(\pm\) 0.04 & 0.56 \(\pm\) 0.04 & 0.48 \(\pm\) 0.03 & 0.38 \(\pm\) 0.02 & 0.50 \(\pm\) 0.03 & 0.38 \(\pm\) 0.03 \\  & CHF II & 1.19 \(\pm\) 0.10 & 1.04 \(\pm\) 0.10 & 0.98 \(\pm\) 0.10 & 0.83 \(\pm\) 0.08 & 0.93 \(\pm\) 0.08 & 0.65 \(\pm\) 0.03 \\ \cline{1-1}  & CHF III & 1.18\(\pm\) 0.12 & 1.04 \(\pm\) 0.11 & 0.97 \(\pm\) 0.11 & 0.79 \(\pm\) 0.12 & 0.91 \(\pm\) 0.12 & 0.65 \(\pm\) 0.06 \\ \cline{1-1}  & CHF IV & 1.20 \(\pm\) 0.23 & 1.07 \(\pm\) 0.23 & 0.98 \(\pm\) 0.21 & 0.82 \(\pm\) 0.16 & 0.92 \(\pm\) 0.13 & 0.66 \(\pm\) 0.05 \\ \cline{1-1}  & \(p\)-value & 0.11 & 0.13 & 0.11 & 0.14 & 0.13 & 0.15 \\ \hline \hline \end{tabular}  
*: statistical difference (\(p\)-value \(<\)0.05); **: significant difference (\(p\)-value \(<\)0.01).  
\end{table} 
Table 7: The statistical F-test results of the sample entropy (SampEn) and fuzzy measure entropy (FuzzyMEn) with different combinations of \(m\) and \(r\) for the different severity levels of congestive heart failure (CHF).