A forward model-based validation of cardiovascular system identification. Export

@article{citeulike:1091594, abstract = {We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data.}, address = {Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, 02139, USA. rmukkama@mit.edu}, author = {Mukkamala, R. and Cohen, R. J.}, citeulike-article-id = {1091594}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/11709441}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=11709441}, issn = {0363-6135}, journal = {Am J Physiol Heart Circ Physiol}, keywords = {autonomic-nervous-system, modelling}, month = {December}, number = {6}, posted-at = {2007-02-07 04:59:32}, priority = {2}, title = {A forward model-based validation of cardiovascular system identification.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/11709441}, volume = {281}, year = {2001} }

TY - JOUR ID - citeulike:1091594 L3 - citeulike-article-id:1091594 N2 - We present a theoretical evaluation of a cardiovascular system identification method that we previously developed for the analysis of beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure, and instantaneous lung volume. The method provides a dynamical characterization of the important autonomic and mechanical mechanisms responsible for coupling the fluctuations (inverse modeling). To carry out the evaluation, we developed a computational model of the cardiovascular system capable of generating realistic beat-to-beat variability (forward modeling). We applied the method to data generated from the forward model and compared the resulting estimated dynamics with the actual dynamics of the forward model, which were either precisely known or easily determined. We found that the estimated dynamics corresponded to the actual dynamics and that this correspondence was robust to forward model uncertainty. We also demonstrated the sensitivity of the method in detecting small changes in parameters characterizing autonomic function in the forward model. These results provide confidence in the performance of the cardiovascular system identification method when applied to experimental data. IS - 6 JF - Am J Physiol Heart Circ Physiol SN - 0363-6135 AD - Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, 02139, USA. rmukkama@mit.edu TI - A forward model-based validation of cardiovascular system identification. VL - 281 KW - autonomic-nervous-system KW - modelling AU - Mukkamala, R AU - Cohen, RJ PY - 2001/12// UR - http://view.ncbi.nlm.nih.gov/pubmed/11709441 ER -