## 4 Discussion  
The main goal of our study was to clarify the cardio-respiratory relationship and its compensatory mechanisms in three different conditions: relaxation, exercise with sub-maximal HR, and post-exercise recovery in an adjusted experimental protocol in young healthy recreative male subjects. To our knowledge, this is the first study which included simultaneous measurements of the heart and respiratory signals in the previously mentioned conditions. In the relaxed state, we did not notice any statistical significance in the 3 min segments in RMSSD, BF, and RCA (Tables 4-6). HR was statistically significant between the first two 3 min segments, but with borderline significance. Potentially, this borderline significance could be attributed to the physiological response of the organism to the environment during the experiment. In support of this statement, the results of the study by [PERSON] et al. indicate significantly higher HR values in subjects measured in clinical settings compared to HR values measured at home [29]. Also, there was no correlation between any of the examined parameters, except for HR and RMSSD, which showed a strong negative correlation (Figure 5). The latter result was expected, as in the relaxed state, the vagal tone of the heart is prevalent and directly influences HR levels [30; 31; 32]. According to the research by [PERSON] and [PERSON] (2019), high vagal activity in the relaxed state is significantly associated with a high exercise capacity [33]. Furthermore, SampEnRR and CrossSampEnRRResp showed higher values, which are indicative of the unpredictability and complexity of heart signals and the asynchrony between the heart and respiratory signals, respectively (Figure 6). In exercise, as expected, the HR value increased, while the parasympathetic regulation of HR decreased (Tables 3 and 4)--the relationship between these parameters ceased to exist at higher HR values. It is well known that a rapid increase in HR is governed by rapid \begin{table}
\begin{tabular}{c l c c c c c c} \hline \hline
**Dependent** & \multirow{2}{*}{**Model**} & \multirow{2}{*}{**Coefficients**} & \multicolumn{4}{c}{**Model Summary**} \\
**Variable** & & & **B** & **SE** & **Beta** & **Sign.** & \(\mathbf{R^{2}}\) & **Sign.** \\ \hline \multirow{6}{*}{BFRec1} & Const & 0.076 & 0.001 & & 0.001 & & \\  & BFRel5 & 0.573 & 0.001 & 0.746 & 0.001 & & \\  & RMSSDExe4 & \(-5.041\) & 0.001 & \(-0.319\) & 0.001 & 1.000 & **0.001** \\  & HHExe4 & 0.001 & 0.001 & 0.072 & 0.001 & & \\  & RCARe13 & 0.001 & 0.001 & 0.007 & 0.001 & & \\ \hline \multirow{6}{*}{BFRec2} & Const & 0.081 & 0.001 & & 0.004 & & \\  & BFRel4 & 0.991 & 0.001 & 0.917 & 0.001 & & \\  & Body Mass & 0.001 & 0.001 & 0.189 & 0.001 & 1.000 & **0.001** \\  & HRExe6 & \(-0.001\) & 0.001 & \(-0.064\) & 0.002 & & \\  & RCAExe2 & \(-0.001\) & 0.001 & \(-0.015\) & 0.008 & & \\ \hline \multirow{6}{*}{BFRec3} & Const & \(-0.141\) & 0.001 & & 0.001 & & \\  & BFRel4 & 1.100 & 0.001 & 0.931 & 0.001 & & \\  & HRRel5 & 0.003 & 0.001 & 0.198 & 0.001 & 1.000 & **0.001** \\  & RCAExe5 & \(-0.002\) & 0.001 & \(-0.037\) & 0.001 & & \\  & HRExe4 & \(6.06\times 10^{-5}\) & 0.001 & 0.005 & 0.002 & & \\ \hline \multirow{6}{*}{BFRec4} & Const & \(-0.125\) & 0.036 & & 0.041 & & \\  & BFRel4 & 0.678 & 0.042 & 0.821 & 0.001 & 0.994 & **0.001** \\  & HRExe1 & 0.003 & 0.001 & 0.312 & 0.008 & & \\ \hline \multirow{6}{*}{BFRec5} & Const & 0.116 & 0.002 & & 0.011 & & \\  & BFRel3 & 0.537 & 0.003 & 0.698 & 0.003 & & \\ \cline{1-1}  & RMSSDExe6 & \(-12.997\) & 0.157 & \(-0.814\) & 0.008 & 1.000 & **0.001** \\ \cline{1-1}  & RMSSDExe4 & 6.432 & 0.137 & 0.450 & 0.014 & & \\ \cline{1-1}  & Body Mass & 0.001 & 0.001 & 0.072 & 0.033 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 10: Multiple linear regression analysis for the averaged BF over 3 min segments during post-exercise recovery in the supine position. parasympathetic withdrawal, as well as by an increased sympathetic tone during physical activity.