Hemodynamic Monitoring for the 21st Century
Professor Ramakrishna Mukkamala,
Department of Electrical and Computer Engineering,
Michigan State University
The projected growth of the elderly population and shortage of clinical staff underscores the need for effective and easy-to-use patient monitoring technologies at the beginning of the 21st century. This need is especially apparent in the context of hemodynamic monitoring of cardiovascular disease. Today, the workhorse in hemodynamic monitoring is the measurement and display of blood pressure waveforms from peripheral arteries, the right heart, and the pulmonary artery. In particular, invasive catheters are broadly utilized in clinical practice to measure blood pressure waveforms at these circulatory sites, while systems have recently been made available to monitor blood pressure waveforms non-invasively from peripheral arteries and chronically from the right ventricle via an implanted device. On the other hand, it is well known that the cardiac output (total blood-flow-rate), left atrial pressure (cardiac preload), ejection fraction (cardiac function), and central aortic blood pressure are more useful in guiding therapy and more predictive of patient outcome. However, these critical central hemodynamic variables conventionally require an operator or an unacceptably high level of invasiveness for their measurement and are therefore not sufficiently monitored in clinical practice. To this end, we introduce novel physiologic-based signal processing techniques to estimate cardiac output, left atrial pressure, ejection fraction, and central aortic blood pressure from the related temporal variations in routinely measured blood pressure waveforms. We demonstrate the validity of these techniques with respect to independent reference measurements from animals and humans over a wide physiologic range. With further development and successful testing, these techniques may ultimately be employed to automatically and less invasively monitor central hemodynamic variables of clinical significance, for the very first time, in various hospital settings, at home, and with implanted devices, so as to help meet the hemodynamic monitoring demands of the 21st century.
Ramakrishna Mukkamala received the B.S.E. degree in biomedical and electrical engineering from Duke University, Durham, NC, in 1993 and the S.M. and Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology, Cambridge, MA, in 1995 and 2000, respectively. He was a Postdoctoral Fellow/Research Engineer in the Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, from 2000 to 2002. Since then, he has been on the faculty of the Department of Electrical and Computer Engineering at Michigan State University, East Lansing, MI, where he is currently an Assistant Professor. His research interests include biomedical signal processing and identification, modeling of physiologic systems, and cardiovascular physiology. He is a recipient of an AHA Scientist Development Grant and research grants from the NIBIB and NHLBI.