Identifying a low-order beat-to-beat model of arterial baroreflex action
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2011
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| Online Access: | http://hdl.handle.net/1721.1/61152 |
| _version_ | 1811074998943612928 |
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| author | Chirravuri, Varun R |
| author2 | George C. Verghese. |
| author_facet | George C. Verghese. Chirravuri, Varun R |
| author_sort | Chirravuri, Varun R |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. |
| first_indexed | 2024-09-23T09:58:46Z |
| format | Thesis |
| id | mit-1721.1/61152 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:58:46Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/611522019-04-12T16:10:04Z Identifying a low-order beat-to-beat model of arterial baroreflex action Identifying a one-pole baroreflex model using l₁-norm minimization Chirravuri, Varun R George C. Verghese. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. 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. 2011-02-23T14:21:08Z 2011-02-23T14:21:08Z 2010 2010 Thesis http://hdl.handle.net/1721.1/61152 698195558 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 147 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Chirravuri, Varun R Identifying a low-order beat-to-beat model of arterial baroreflex action |
| title | Identifying a low-order beat-to-beat model of arterial baroreflex action |
| title_full | Identifying a low-order beat-to-beat model of arterial baroreflex action |
| title_fullStr | Identifying a low-order beat-to-beat model of arterial baroreflex action |
| title_full_unstemmed | Identifying a low-order beat-to-beat model of arterial baroreflex action |
| title_short | Identifying a low-order beat-to-beat model of arterial baroreflex action |
| title_sort | identifying a low order beat to beat model of arterial baroreflex action |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/61152 |
| work_keys_str_mv | AT chirravurivarunr identifyingaloworderbeattobeatmodelofarterialbaroreflexaction AT chirravurivarunr identifyingaonepolebaroreflexmodelusingl1normminimization |