title: Recursive identification of an arterial baroreflex model for the evaluation of cardiovascular autonomic modulation.
abstract: The evaluation of the time-varying vagal and sympathetic contributions to heart rate remains a challenging task because the observability of the baroreflex is generally limited and the time-varying properties are difficult to take into account, especially in non-stationnary conditions. The objective is to propose a model-based approach to estimate the autonomic modulation during a pharmacological challenge. A recursive parameter identification method is proposed and applied to a mathematical model of the baroreflex, in order to estimate the time-varying vagal and sympathetic contributions to heart rate modulation during autonomic maneuvers. The model-based method was evaluated with data from five newborn lambs, which were acquired during injection of vasodilator and vasoconstrictor drugs, on normal conditions and under beta-blockers, so as to quantify the effect of the pharmacological sympathetic blockade on the estimated parameters. After parameter identification, results show a close match between experimental and simulated signals for the five lambs, as the mean relative root mean squared error is equal to 0.0026 (± 0.003). The error, between simulated and experimental signals, is significantly reduced compared to a batch identification of parameters. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge and, as expected, it was possible to observe an alteration of the sympathetic response under beta-blockers. The simulated vagal modulation illustrates a response similar to traditional heart rate variability markers during the pharmacological maneuver. The model-based method, proposed in the paper, highlights the advantages of using a recursive identification method for the estimation of vagal and sympathetic modulation.
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France. Electronic address: virginie.lerolle@univ-rennes1.fr.
authors.forename: Virginie
authors.initials: V
authors.lastname: Le Rolle
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France; CHU Rennes, Pole de pdiatrie mdico-chirurgicale et gntique clinique - Service de pdiatrie, Rennes F-35000, France.
authors.forename: Alain
authors.initials: A
authors.lastname: Beuchee
authors.affiliation: Department of Pediatrics, University of Sherbrooke, QC, Canada J1H5N4.
authors.forename: Jean-Paul
authors.initials: JP
authors.lastname: Praud
authors.affiliation: Department of Pediatrics, University of Sherbrooke, QC, Canada J1H5N4.
authors.forename: Nathalie
authors.initials: N
authors.lastname: Samson
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France; CHU Rennes, Pole de pdiatrie mdico-chirurgicale et gntique clinique - Service de pdiatrie, Rennes F-35000, France.
authors.forename: Patrick
authors.initials: P
authors.lastname: Pladys
authors.affiliation: INSERM, U1099, Rennes F-35000, France; Campus de Beaulieu, Université de Rennes 1, LTSI, 263 Avenue du General Leclerc, CS 74205, 35042 Rennes Cedex, Rennes F-35000, France.
authors.forename: Alfredo I
authors.initials: AI
authors.lastname: Hernández
mesh_terms: D000319:Adrenergic beta-Antagonists / Q000627:therapeutic use; D000465:Algorithms; D000818:Animals; D000831:Animals, Newborn; D001341:Autonomic Nervous System / Q000502:physiology*; D017704:Baroreflex / Q000502:physiology*; D001794:Blood Pressure / Q000502:physiology; D002319:Cardiovascular System; D006339:Heart Rate; D008955:Models, Cardiovascular; D012756:Sheep; D012984:Software; D014630:Vagus Nerve / Q000502:physiology
chemical_list: D000319:Adrenergic beta-Antagonists
keywords: Autonomic nervous system; Heart rate variability; Model-based analysis; Parameter identification; Physiological modeling; Reccursive identification