New signal processing techniques for improved precision of noninvasive impedance cardiography

Abstract

Impedance cardiographic determination of clinically important cardiac parameters such as systolic time intervals, stroke volume, and related cardiovascular parameters has not yet found adequate application in clinical practice, since its theoretical basis remains controversial, and the precision of beat-to-beat parameter estimation has until recently suffered under severe shortcomings of available signal processing techniques. High levels of noise and motion artifacts deteriorate signal quality and result in poor event detection. To improve the precision of impedance cardiography, new techniques for event detection and parameter estimation have been developed. Specifically, matched filtering and various signal segmentation and decomposition techniques have been tested on impedance signals with various levels of artificially superimposed noise and on actual recordings from subjects in a laboratory study of cardiovascular response to a cognitive challenge. Substantial improvement in the precision of impedance cardiography was obtained using the newly developed signal processing techniques. In addition, some preliminary evidence from comparisons of the impedance cardiogram with invasive aortic electromagnetic flow measurement in anesthetized rabbits is presented to address questions relating to the origin of the impedance signal.