Improving cardiovascular monitoring through modern techniques

Abstract

This article presents two applications of modern processing techniques for cardiovascular monitoring. These two applications are quite different in terms of theory as well as application, but they nevertheless present similarities. In both cases, the incentive for using new techniques came from the need for higher performance in order to achieve desired goals. The results obtained are not limited to the particular cases presented here and may lead to original developments in pure signal processing. The first application deals with automatic in-vivo estimation of microvascular pulmonary pressure (P/sub mv/). New structures of multirate adaptive filtering based on wavelet packets have been developed to remove the respiratory artifact present. The other application investigates the possibility of using chaos and fractal theory to analyze heart rate variability. The use of chaos might help predict cardiac events, such as ventricular tachycardia or fibrillation, with better accuracy than conventional methods.