Quantitative analysis of heart rate baroreflex in healthy subjects using adaptive neuro fuzzy inference system approximation

This paper is focused on the identification of the heart rate (HR) baroreflex mechanism using new nonlinear system identification approach. The proposed HR baroreflex model is based on inherent features of the autonomic nervous system for which we develop an adaptive neuro-fuzzy inference system (ANFIS) structure. The simulation results show significant improvements in prediction of HR as a model output by calculating the normalized root mean square error (NRMSE) in comparison with other reported methods. We have shown that for modeling of cardiovascular system regulation, our proposed nonlinear model is more accurate than other recently developed methods.