2026-09-19T13:31:40Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/611522022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
George C. Verghese.
Chirravuri, Varun R
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2011-02-23T14:21:08Z
2011-02-23T14:21:08Z
2010
2010
http://hdl.handle.net/1721.1/61152
698195558
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 127-133).
The arterial baroreflex is a fast-acting control mechanism that the body relies on to regulate blood pressure. Previous efforts to quantitatively model the baroreflex have relied primarily on non-parametric characterization of the transfer function from blood pressure to heart rate (Berger et al.,1989, Akselrod et al., 1981,1985). Of the parametric models proposed, most focus on matching empirical transfer functions with continuous-time models (Berger et al., 1991). Use of these models is often restricted to simulation, and consequently not focused on prediction. We develop a beat-to-beat, one-pole model for the baroreflex that can parsimoniously capture both the empirical frequency-domain and time-domain characteristics of the baroreflex. Further, we develop a robust identification method for on-line estimation of our model parameters from clinical data. We conclude by presenting preliminary results of our model and estimation method applied to patients undergoing drug-induced autonomic blockade.
by Varun R. Chirravuri.
M.Eng.
147 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Identifying a low-order beat-to-beat model of arterial baroreflex action
Identifying a one-pole baroreflex model using l₁-norm minimization
Thesis
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<Abstract>The arterial baroreflex is a fast-acting control mechanism that the body relies on to regulate blood pressure. Previous efforts to quantitatively model the baroreflex have relied primarily on non-parametric characterization of the transfer function from blood pressure to heart rate (Berger et al.,1989, Akselrod et al., 1981,1985). Of the parametric models proposed, most focus on matching empirical transfer functions with continuous-time models (Berger et al., 1991). Use of these models is often restricted to simulation, and consequently not focused on prediction. We develop a beat-to-beat, one-pole model for the baroreflex that can parsimoniously capture both the empirical frequency-domain and time-domain characteristics of the baroreflex. Further, we develop a robust identification method for on-line estimation of our model parameters from clinical data. We conclude by presenting preliminary results of our model and estimation method applied to patients undergoing drug-induced autonomic blockade.</Abstract>
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