## 4 Discussion  
The objective of this work was to indirectly assess the modulatory activity of the ANS in ESRD patients through a spectrotemporal analysis of HRV and to evaluate the behavior of the mean R-R intervals (both during hemodiafiltration). The participants included patients who experienced an intradialytic hypotension event and patients who did not. This characteristic allowed us to split the participants into two groups and study the differences in the modulatory response of the SNS and PNS when this adverse event occurs. Furthermore, we also showed the feasibility of using 10 min epochs overlapping by 40% to perform the analyses and reduce the errors in the spectral estimation of VLF power. The results obtained with the mean R-R intervals show visual and statistical differences between the groups, which indicate that it is possible to use this measure to discriminate between hypotensive and non-hypotensive patients. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Variable** & **Quadratic Model** & \(R\) & \(R^{2}\) & \(p\) & **Achieved Statistical Power** \\ \hline Mean R-R & \(883.36-0.244-0.0005\)\({}^{2}\) & 0.65 & 0.42 & \(\ll\)0.05 & 0.98 \\ VLF & \(557.04+10.60r-0.050\)\({}^{2}\) & 0.53 & 0.28 & 0.01 & 0.83 \\ LF & \(556.29+7.27t-0.052\)\({}^{2}\) & 0.68 & 0.46 & \(\ll\)0.05 & 0.99 \\ HF & \(157.17+0.84t-0.009t\)\({}^{2}\) & 0.69 & 0.48 & \(\ll\)0.05 & 0.99 \\ LF/HF & \(6.33+0.04t-0.0002\)\({}^{2}\) & 0.31 & 0.10 & 0.23 & 0.32 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Quadratic regression models, statistical parameters achieved and statistical power for the hypotensive group. Variable \(t\) represents time. \(p<0.05\) was considered significant. Figure 5: Changes of the LH/HF ratio over time for the hypotensive (blue plots) and non-hypotensive (red plots) groups. Solid lines correspond to the quadratic models and dashed lines to the confidence intervals. Data are scattered for the hypotensive group. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Variable** & **Quadratic Model** & \(R\) & \(R^{2}\) & \(p\) & **Achieved Statistical Power** \\ \hline Mean R-R & \(757.56+2.18t-0.011t\)\({}^{2}\) & 0.95 & 0.90 & \(\ll\)0.05 & 1.00 \\ VLF & \(5148.88+20.87t-0.092t\)\({}^{2}\) & 0.81 & 0.66 & \(\ll\)0.05 & 0.99 \\ LF & \(475.13+7.88t-0.027t\)\({}^{2}\) & 0.77 & 0.59 & \(\ll\)0.05 & 0.99 \\ HF & \(153.67+6.76t-0.030t\)\({}^{2}\) & 0.87 & 0.76 & \(\ll\)0.05 & 1.00 \\ LF/HF & \(3.84-0.03t+0.0001t\)\({}^{2}\) & 0.69 & 0.48 & \(\ll\)0.05 & 0.99 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Quadratic regression models, statistical parameters and achieved statistical power for the non-hypotensive group. Variable \(t\) represents time. \(p<0.05\) was considered significant. To assess the spectrotemporal distribution of power, we used the STFT due to its ability to operate over short segments of a signal that can be considered stationary and linear. This characteristic diminishes the difficulties found in analyzing HRV because of the dynamics present in the CV system. Other advantages of the STFT are its low computational load compared to other time-frequency analysis tools [23; 33] and its lower amount of spectral leakage resulting from the use of a single epoch to perform the analysis [38], which allows the identification of large spectral components present in noisy signals. The time-frequency analysis was performed using 10 min segments of HRV. According to the guidelines published in 1996 by the joint American and European Task Force for HRV Analysis [13], this spectral analysis can be performed in either short-term recordings 2 to 5 min in length or long-term recordings of 24 h in length. When short-term recordings were used, the guidelines indicated that it is possible to estimate the power spectrum in the LF, HF, and VLF bands; however, it is also advised in the guidelines that the results obtained for the VLF power are not reliable; hence, its estimation must be avoided.