Abstract : Short-term interaction between heart rate (HR) and physiological measures like blood pressure and respiration reveals relevant information about autonomic nervous system (ANS) function. Complex mathematical models for describing their couplings have been proposed in the literature. However, an accurate estimation of their parameters in an inverse modeling problem is crucial to extract reliable ANS related indices. This study considers a physiologically-based model of the cardiovascular- respiratory system and ANS control that presents the neural and mechanical effects of respiration separately. The estimation method is evaluated on synthetic signals. An accurate estimation of the highest-sensitivity model parameter (intrinsic HR) is achieved with an error of 4.7 ± 3.4% over the actual values. One of the parameters reflecting the amplitude of the respiratory-mediated variations presents an even better approximation with a mean relative error as low as 3.8 ± 3.3%. Our results show that most of the high-sensitivity parameters and also respiratory- related parameters that are specifically considered in our physiologically-based framework can be well approximated regardless of their initial values.