## 3 Methodology
### Identification of UC-Deceleration Episodes  
As explained at the beginning of Section 3, the main purpose of this work was to investigate whether, by separately analyzing the complete signal (CS), during decelerations (DD), and during resting (DR) periods, the CTG classification could improve compared with analyzing only the complete signal. Therefore, it is necessary to identify the FHR decelerations in order to differentiate them from the resting periods. The method proposed for deceleration identification is explained using the signals  
Figure 5: Example of the FHR signal decomposition operation and spectral analysis, one row for each intrinsic mode function (IMF). (**left** column) IMFs (IMF\({}_{1}\)...IMF\({}_{10}\)) computed from the detrended FHR signal presented in Figure 4b; (**right** column) time-varying (TV-AR) spectrum computed from each IMF.  
presented in Figure 6a, which correspond to the preprocessed FHR signal and floating-line computed in Section 3.2.2.  
For the deceleration episodes' identification, we propose a new concept: the UC-deceleration episodes. This concept not only considers evident decelerations as defined in guidelines (\(>\)15 bpm in amplitude and \(>\)15 s length) [1] but also considers the UCs as stimuli that excite a fetal response.  
Following [56], the identification of UC-deceleration episodes is performed in two steps. First, evident deceleration episodes are detected by using the floating-line (described in Section 3.2.2) and a _progressive baseline_ (described below). Then, episodes that were not recognized in the previous step are identified considering the UCs stimuli.  
In the first step, we propose computing a progressive baseline (PBL), which allows recognizing evident deceleration episodes. This proposed PBL is computed as follows:  
1. A virtual baseline (VBL) is estimated by filtering the FHR signal using the same median filter for the floating-line computation but with a different sliding window. Following [65], the sliding window size was set to 400 s length.
2. Then, the VBL allows defining a range in amplitude delimit by the low (\(L\)) and high (\(H\)) traces, which corresponds to the signal data that will be considered for the PBL computation. These traces are described by Equations (8) and (9), where \(n\) corresponds to the sample number, and \(\Delta\)FHR is set to 10 bpm following [66]. \[L(n)=\text{VBL}(n)-\Delta\text{FHR}.\] (8) \[H(n)=\text{VBL}(n)+\Delta\text{FHR}.\] (9)
3. Finally, the PBL is computed by considering only the data described by \(\text{FHR}_{LH}\) (see Equation (10)) by using the same median filter used for the VBL extraction.  
\[\text{FHR}_{LH}(n)=\begin{cases}L(n)&\text{FHR}(n)<L(n)\\ \text{FHR}(n)&L(n)\leq\text{FHR}(n)\leq H(n)\\ H(n)&\text{FHR}(n)>H(n).\end{cases} \tag{10}\]  
For the evident decelerations' detection, the PBL is used as a threshold over the floating-line. Differences of more than 15 bpm in amplitude and more than 15 s length [1] are detected as evident decelerations. The computed PBL and evident deceleration episodes are plotted in Figure 6b in magenta and black, respectively.  
The second step allows the identification of the episodes that were not recognized as evident decelerations, but that are certainly response to UC events. These episodes, also called _UC-segments_, are defined following the criteria proposed in [13], which correspond to FHR signal segments starting 7 s before a UC apex and ending 50 s after it. First, UC apexes of significant amplitude (i.e., \(\geq\)30 mmHg) are detected and considered for this operation. Figure 6c shows the preprocessed UC signal (described in Section 3.2.1) and the detected UC apexes. Then, when an evident deceleration was not recognized, but a UC apex was detected, its corresponding uc-segment was added to be considered for the analysis. The complete set of uc-deceleration episodes is presented in Figure 6d. Here, we can observe that episodes D01, D02, D05, and D06, which were not recognized as evident decelerations, were included in this second identification step.