Identification of cardiovascular baroreflex for probing homeostatic stability

This paper presents a method to identify the cardiovascular baroreflex parameters that are useful for probing homeostatic stability. The work is built upon a physiology-based model of the closed-loop cardiovascular and baroreflex feedback system describing the regulation of heart rate and blood pressure. Parametric sensitivity analysis is conducted on the model to classify the model parameters into high-sensitivity, low-sensitivity, and invariant groups based on their relative impacts on the system outputs. The baroreflex identification is formulated as a nonlinear optimization problem in which only high-sensitivity model parameters are identified whereas low-sensitivity and invariant parameters are fixed at their typical values. The advantage of the method is its computational efficiency without significant compromise in performance and accuracy. The method was applied to the experimental data of 10 individuals in the MIMIC Database in the PhysioBank. The promising results suggest potential of the proposed method in probing homeostasis based on the estimates of sympathetic and parasympathetic tones.