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Active Non-Intrusive System Identification for Cardiovascular Monitoring: Part II — Development of System Identifiction Algorithm

[+] Author Affiliations
Nima Fazeli, Jin-Oh Hahn

University of Maryland, College Park, MD

Paper No. DSCC2013-3850, pp. V003T43A004; 10 pages
  • ASME 2013 Dynamic Systems and Control Conference
  • Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control
  • Palo Alto, California, USA, October 21–23, 2013
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5614-7
  • Copyright © 2013 by ASME


In this paper, we present an innovative active non-intrusive system identification approach to cardiovascular monitoring. The proposed approach is based on a dual collocated actuator-sensor system for cardiovascular system identification, in which the actuators actively excite the arterial tree to create rich and informative trans-mural pressure waves traveling in the arterial tree, which are then non-intrusively measured by the collocated sensors. In our previous work, we developed a mathematical model to reproduce the propagation of intra-vascular (arterial) and extra-vascular (artificial) pressure waves along the arterial tree. Then, we used a dual (radial-femoral) blood pressure cuff system as a prototype dual collocated actuator-sensor system to demonstrate the proposed methodological framework to create rich trans-mural pressure waves as well as to non-intrusively reconstruct them from sensor measurements. In this follow-up work, we propose a novel system identification algorithm to derive cardiovascular system dynamics and reconstruct central aortic blood pressure waveform from the trans-mural pressure waves observed at the peripheral locations. It was successfully demonstrated that the system identification algorithm was able to reconstruct the central aortic blood pressure accurately, and that its performance was superior to the passive non-intrusive approach.

Copyright © 2013 by ASME



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