## 3 Materials and Methods
### Feature Extraction  
We extracted 20 HRV features from each of the 5 min RRI segments as input data for the feature-based prediction model (Figure 1, Table 2) [17]. We followed the international guidelines for a standard HRV analysis in feature extraction [10,47], which was performed using the Neurokit2 package [44]. [PERSON] et al. demonstrated that linear and nonlinear HRV features evaluated based on 5 min recordings showed significant dependence on age in healthy subjects, suggesting that the length of the signal was long enough to reflect age-induced variation in HRV features [18].  
Six time-domain features were calculated directly from the RRI series: the mean of the RRIs, standard deviation of the RRIs (SDNN), root mean square of successive RRI differences (RMSSD), percentage of successive RRIs differing by more than 50 ms (pNN50), integral of the histogram of the RRI divided by its height (TRI), and baseline width of the RRI histogram (TINN). Seven features were calculated using frequency-domain analysis. The RRI data were interpolated at 4 Hz using quadratic spline interpolation. Subsequently, [PERSON]'s method was used to estimate the power spectral density (PSD) of equidistantly sampled RRI data. The following features were evaluated from the PSD: logarithm-transformed powers of very-low-frequency (VLF, 0-0.04 Hz), low-frequency (LF, 0.04-0.15 Hz), high-frequency (HF, 0.15-0.4 Hz), and total bands. Additionally, the relative powers of the LF and HF bands in normalized units and the LF/HF power ratio were evaluated. Five nonlinear features were extracted to assess the nonlinear dynamics in the RRI series: approximate entropy (ApEn) [48], sample entropy (SampEn) [49], short- and long-range scaling exponents of detrended fluctuation analysis (DFA) [50], and correlation dimension (CorDim) [51]. Finally, two features were evaluated using a Poincare plot. SD1 and SD2 represent the standard deviations of the Poincare plot perpendicular to and along the identity line, respectively.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Feature** & **Description** \\ \hline \hline
**Time-domain** & \\ \hline RRI (ms) & Mean RR intervals \\ SDNN (ms) & Standard deviation of RR intervals \\ RMSSD (ms) & Root mean square of successive RR interval differences \\ pNN50 (\%) & Percentage of successive RR intervals differing more than 50 ms \\ TRI & Integral of the histogram of the RR interval divided by its height \\ TINN (ms) & Baseline width of the RR interval histogram \\ \hline \hline
**Frequency-domain** & \\ \hline logVLF (s\({}^{2}\)) & Logarithm-transformed power in the VLF band (0–0.04 Hz) \\ logLF (s\({}^{2}\)) & Logarithm-transformed power in the LF band (0.04–0.15 Hz) \\ LFnu (nu) & Relative power of the LF band \\ logHF (s\({}^{2}\)) & Logarithm-transformed power in the HF band (0.15–0.4 Hz) \\ HFnu (nu) & Relative power of the HF band \\ LF/HF & Ratio between LF and HF band powers \\ logTot (s\({}^{2}\)) & Logarithm-transformed total power \\ \hline \hline
**Nonlinear domain and Poincaré plot** & \\ \hline ApEn & Approximate entropy \\ SampEn & Sample entropy \\ \(\alpha\)1 & Short-term scaling exponent of DFA \\ \(\alpha\)2 & Long-term scaling exponent of DFA \\ CorDim & Correlation dimension \\ SD1 (ms) & Standard deviation of the Poincaré plot perpendicular to the line of identity \\ SD2 (ms) & Standard deviation of the Poincaré plot along the line of identity \\ \hline \hline \end{tabular}
\end{table}
Table 2: Description of HRV features.