Title :
Robust model-based estimators for cardiac nerve activity
Author :
Radu, Cristian M. ; Kaplan, Daniel T.
Author_Institution :
Dept. of Physiol., McGill Univ., Montreal, Que., Canada
Abstract :
This paper outlines our design of a continuous estimator for the sympathetic innervation of the heart. The estimator is computed by linear methods, yet it is tested on a nonlinear, detailed model of cardiovascular and respiratory dynamics. Inverting a model output (blood pressure) to recover internal activity by means of the H∞ and structured singular value (μ) design methods, allows direct treatment of signal and model uncertainty (noise and nonlinearity, respectively), in a computationally convenient, linear way. Numerical simulations suggest that the variability of the blood pressure signal can be decoded to yield good estimates of nerve activity despite parametric uncertainty, in a range of physiological conditions
Keywords :
biocontrol; cardiology; estimation theory; haemodynamics; neurophysiology; physiological models; pneumodynamics; blood pressure; cardiac nerve activity; cardiovascular dynamics; continuous estimator; heart; internal activity; linear methods; model uncertainty; noise; nonlinear model; parametric uncertainty; physiological conditions; respiratory dynamics; robust model-based estimators; signal uncertainty; structured singular value design methods; sympathetic innervation; Blood pressure; Cardiology; Decoding; Design methodology; Heart; Numerical simulation; Robustness; Testing; Uncertainty; Yield estimation;
Conference_Titel :
Engineering in Medicine and Biology Society, 1995., IEEE 17th Annual Conference
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7803-2475-7
DOI :
10.1109/IEMBS.1995.579786
