## 4 Discussion
[31], who reported an analysis of R-R intervals in short-term recordings acquired at the beginning, middle, and end of HD therapy. Even though we used more analysis points obtained over longer epochs (30 points obtained from overlapping segments of 10 min each versus three points from non-overlapping segments of 5 min segments each), we found significant differences (\(p<0.05\)) between hypotensive and non-hypotensive patients for the mean R-R intervals obtained both in the middle and at the end of the therapy. The results of the spectral analysis agree in terms of behavior and significant differences for each of the three bands evaluated. An important characteristic to mention is that both our studies used absolute spectral power (ms\({}^{2}\)/Hz) to compare the two groups of patients. On the contrary, the results of the spectral analysis published by [PERSON] et al. [8] show that when a hypotension event occurs, the LF power decreases, and the HF power increases (both greatly) compared to their respective values in the middle of therapy; for those patients who did not experience a hypotension event, the LF power increases, and the HF decreases at the end of the therapy compared to their respective values in the middle of therapy. This difference with our results might be attributable to the normalization procedure the authors used before comparing the spectral power from hypotensive and non-hypotensive patients. Both studies also had a similar number of patients (20 in this work and 19 in [PERSON] research). Another interesting result we found is that the LF/HF ratio is very scattered in hypotensive patients, which explains the low correlation and determination coefficients obtained with this model. The high dispersion of these measurements could be associated with dysfunction in the autonomic regulation of these patients, which greatly attenuates HF's power. On the contrary, the LF/HF ratio shows much less dispersion in non-hypotensive patients and can be well adjusted to a quadratic regression model. It is worth noting that each group of patients has different average LF/HF ratios during therapy. For hypotensive patients, this ratio is close to 8, while for non-hypotensive patients, it is close to 3. The results presented in this work show that the decompensation of the CV system during HD therapy, leading to a hypotension event in some patients, is reflected by the modulatory activity of the SNS and PNS through changes in the magnitude of the spectral power in the VLF, LF, and HF bands over time. These differences can be evaluated through the application of the STFT, by allowing to know the dynamics of the HRV through time. Two points that stand out in the time-frequency analysis with the STFT are related to the length of the window chosen for performing STFT since this length determines the time-frequency resolution, and the window function was employed because the spectral leakage depends on this function. In our application, the length of the window was determined by the size of the epoch required to decrease the error in the VLF power estimation to at least 20%, and the window function chosen was the Hanning or Raised-Cosine window due to its minimal spectral leakage [38]. A limitation of our study is the relatively small size of our population (N = 20, 8 hypotensive versus 12 non-hypotensive). Despite this small number of participants, the differences found in the spectral analysis are clear enough to discriminate patients who experienced hypotension events from those who did not. With regard to the time-frequency analysis tools, we acknowledge that there are other alternatives to the STFT, including the wavelet transform, the Hilbert-Huang transform [23], and the synchrosqueezed transform [40]. Further studies are required to compare the estimation of the spectrotemporal power of HRV during HD with the other time-frequency analysis tools, and to assess their effectiveness. In this work, we chose the STFT because of its simplicity and low computational cost.