## 3 Results
### Evaluation of Proposed Cardio Data Protection Procedure  
An evaluation of the proposed procedure for encryption of cardio signals in the implementation of different lengths of the built-in watermark has been made (Table 6). The results were obtained by applying the procedure on the PPG data. The parameters in Table 7 were obtained from evaluating 24 PPG signals (each signal represented 2 h of recording). The results in Table 7 show a high degree of compression when using the Haar transformation, but worsened values for the other estimation parameters. The application of the Db4 transformation in the implementation of the presented method proved to be the most optimal in terms of the obtained values of the studied parameters (almost the same results are obtained with Db8). The application of Daubechies wavelet transform with more coefficients than eight leads to a deterioration of the studied parameters. The dependence of MSE on the selected algorithm of threshold processing of the coefficients in the compression step of the proposed method was studied. The initial ECG data examined are shown in Figure 4, while Figure 5 shows a graph of the reconstructed data. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Watermark** & **32** & **64** & **128** & **256** & **512** \\
**Length** & & & & & \\ \hline PSNR [db] & 45.33 & 44.44 & 43.62 & 42.33 & 41.51 \\ MSE & 0.043 & 0.047 & 0.051 & 0.058 & 0.063 \\ PRD [\%] & 5.14 & 5.86 & 6.31 & 6.87 & 6.99 \\ RMSE & 0.2074 & 0.2168 & 0.2258 & 0.2408 & 0.251 \\ MAPE [\%] & 0.0041 \(\pm\) 0.001 & 0.0046 \(\pm\) 0.002 & 0.013 \(\pm\) 0.002 & 0.11 \(\pm\) 0.003 & 0.21 \(\pm\) 0.007 \\ BER & 0.005 & 0.08 & 0.11 & 0.18 & 0.22 \\ KLD & 0.002 & 0.006 & 0.014 & 0.06 & 0.08 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Evaluation parameters for different watermark lengths. Figure 4: Graph of original ECG signal. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Wavelet Basis** & **Db2 (Haar)** & **Db4** & **Db8** & **Db12** & **Db16** \\ \hline PSNR [db] & 14.81 \(\pm\) 1.19 & 52.03 \(\pm\) 0.81 & 51.16 \(\pm\) 0.47 & 45.32 \(\pm\) 0.31 & 44.65 \(\pm\) 0.88 \\ MSE & 0.91 \(\pm\) 0.08 & 0.022 \(\pm\) 0.001 & 0.024 \(\pm\) 0.002 & 0.043 \(\pm\) 0.02 & 0.046 \(\pm\) 0.001 \\ PRD [\%] & 16.88 \(\pm\) 3.74 & 5.91 \(\pm\) 0.99 & 6.12 \(\pm\) 1.02 & 6.82 \(\pm\) 1.11 & 6.94 \(\pm\) 1.03 \\ RMSE & 0.956 \(\pm\) 0.11 & 0.1483 \(\pm\) 0.03 & 0.1549 \(\pm\) 0.04 & 0.2047 \(\pm\) 0.07 & 0.2145 \(\pm\) 0.07 \\ MAPE [\%] & 0.33 \(\pm\) 0.04 & 0.0047 \(\pm\) 0.0008 & 0.0051 \(\pm\) 0.001 & 0.0054 \(\pm\) 0.01 & 0.062 \(\pm\) 0.03 \\ BER & 0.41 \(\pm\) 0.1 & 0.011 \(\pm\) 0.03 & 0.014 \(\pm\) 0.08 & 0.017 \(\pm\) 0.09 & 0.024 \(\pm\) 0.01 \\ KLD & 0.36 \(\pm\) 0.01 & 0.006 \(\pm\) 0.01 & 0.014 \(\pm\) 0.002 & 0.011 \(\pm\) 0.02 & 0.06 \(\pm\) 0.003 \\ CR & 6.68 \(\pm\) 0.84 & 4.18 \(\pm\) 0.53 & 4.16 \(\pm\) 0.72 & 3.99 \(\pm\) 0.32 & 3.81 \(\pm\) 0.41 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Estimation parameters for different wavelet basis. Figures 6 and 7 present the MSE obtained from the reconstruction of the ECG signal data (shown in Figure 4). The calculations were performed on the basis of the initial input ECG signal and the received output ECG signal. The research aims to demonstrate both the values of the obtained MSE between the input and output signal and the differences in the MSE (graphically represented) using the amplitude method of reduction of the coefficients (Figure 6) and the EPE method (Figure 7). The comparison between the two graphs shows significantly lower MSE values when using the EPE method. It is worth discussing the analysis of the PRD parameter for different methods of threshold processing. Figure 8 shows a graph of the dependence of the PRD parameter (determined in the output-transformed signal) and the compression ratio when using the amplitude method of threshold processing.