Linear and nonlinear system identification of autonomic heart-rate modulation.

Abstract

The authors' findings show that system identification provides a useful, noninvasive, and quantitative means for evaluating cardiovascular regulatory mechanisms. With combinations of linear and nonlinear identification, new insights about the cardiovascular regulatory dynamics were obtained. System identification provides a new way of studying and monitoring cardiovascular function. Instead of just studying the signals generated by the cardiovascular regulatory system, the signals are analyzed to characterize quantitatively the mechanisms that generate them. System identification is a type of inverse modelingin which the physiologic signals are used to create a model of cardiovascular regulation for the specific individual from whom the data are obtained. As such, system identification would appear to be a desirable means for evaluating effects of physiologic alterations resulting from pharmacological interventions, changes in environment such as changes in gravitational field, physiologic stresses such as hypoxia and exercise, and disease processes. System identification may also prove to be an attractive means to study closed-loop regulation in other physiologic systems, ranging in size from biochemical pathways to intact multi-organ systems.