Correlation between vector autoregressive model coefficients of circulatory system and baroreflex sensitivity

In this study, heart rate variability (RR) and systolic blood pressure (SBP) signals are considered as a two-channel signal. The two-channel signal has been represented by a first-order vector autoregressive model (VAR(1)) and autoregressive exogenous model (ARX), and baroreflex sensitivity (BRS) has been computed. This processing has been repeated for 17 subjects whose blood pressure has been altered with medicine (phenylephrine) injection and BRS, and VAR(1) model parameters have been related by employing multi-variable linear regression. The correlation coefficient between predicted BRS in this way and computed BRS has been obtained as 0.73. When linear relationship between BRS and VAR(1) model coefficients were examined, the correlation coefficient between BRS and b coefficient was found as 0.8132. The same study was repeated using ARX model and the correlation coefficient between BRS was found to be 0.72. The correlation coefficient between BRS and a12 coefficient of ARX model was found as 0.8096. These results shows that BRS can be predicted from VAR(1) and ARX model coefficients, and the used models characterize the circulatory system.