{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/61152"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/61152","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Identifying a low-order beat-to-beat model of arterial baroreflex action","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_html":"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_has_math":false,"creators":["Chirravuri, Varun R"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["George C. Verghese."],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010","date_published":"2010","updated_at":"2026-07-22T22:21:08Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/61152","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["George C. Verghese."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."]},{"key":"dc:creator","label":"Author","values":["Chirravuri, Varun R"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2011-02-23T14:21:08Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2011-02-23T14:21:08Z"]},{"key":"dc:date.issued","label":"Date","values":["2010"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical Engineering and Computer Science."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["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."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/61152"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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)."]},{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["Identifying a low-order beat-to-beat model of arterial baroreflex action"]}]}],"canonical_facts":{"dc:contributor.advisor":["George C. Verghese."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:creator":["Chirravuri, Varun R"],"dc:date.accessioned":["2011-02-23T14:21:08Z"],"dc:date.available":["2011-02-23T14:21:08Z"],"dc:date.issued":["2010"],"dc:description":["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)."],"dc:description.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."],"dc:description.degree":["M.Eng."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/61152"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Electrical Engineering and Computer Science."],"dc:title":["Identifying a low-order beat-to-beat model of arterial baroreflex action"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:08Z"}