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This Article Full Text Full Text (PDF) All Versions of this Article: 294/1/H293    most recent 00852.2007v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in ISI Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Chen, X. Articles by Mukkamala, R. Search for Related Content PubMed PubMed Citation Articles by Chen, X. Articles by Mukkamala, R.

Estimation of the total peripheral resistance baroreflex impulse response from spontaneous hemodynamic variability

¹Department of Electrical and Computer Engineering, Michigan State University, East Lansing; and ²Departments of Physiology and ³Surgery, Wayne State University School of Medicine, Detroit, Michigan

Submitted 21 July 2007 ; accepted in final form 29 October 2007

We previously developed a mathematical analysis technique for estimating the static gain values of the arterial total peripheral resistance (TPR) baroreflex (G_A) and the cardiopulmonary TPR baroreflex (G_C) from small, spontaneous beat-to-beat fluctuations in arterial blood pressure, cardiac output, and stroke volume. Here, we extended the mathematical analysis so as to also estimate the entire arterial TPR baroreflex impulse response [h_A(t)] as well as the lumped arterial compliance (AC). The extended technique may therefore provide a linear dynamic characterization of TPR baroreflex systems during normal physiological conditions from potentially noninvasive measurements. We theoretically evaluated the technique with respect to realistic spontaneous hemodynamic variability generated by a cardiovascular simulator with known system properties. Our results showed that the technique reliably estimated h_A(t) [error = 30.2 ± 2.6% for the square root of energy (E_A), 19.7 ± 1.6% for absolute peak amplitude (P_A), 37.3 ± 2.5% for G_A, and 33.1 ± 4.9% for the overall time constant] and AC (error = 17.6 ± 4.2%) under various simulator parameter values and reliably tracked changes in G_C. We also experimentally evaluated the technique with respect to spontaneous hemodynamic variability measured from seven conscious dogs before and after chronic arterial baroreceptor denervation. Our results showed that the technique correctly predicted the abolishment of h_A(t) [E_A = 1.0 ± 0.2 to 0.3 ± 0.1, P_A = 0.3 ± 0.1 to 0.1 ± 0.0 s^–1, and G_A = –2.1 ± 0.6 to 0.3 ± 0.2 (P < 0.05)] and the enhancement of G_C [–0.7 ± 0.44 to –1.8 ± 0.2 (P < 0.05)] following the chronic intervention. Moreover, the technique yielded estimates whose values were consistent with those reported with more invasive and/or experimentally difficult methods.

autonomic nervous system; hemodynamics; modeling; system identification; transfer function