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SHR Neuro Cancer Cardio Lipid Metab Microb

Batzel, J; Baselli, G; Mukkamala, R; Chon, KH.
Modelling and disentangling physiological mechanisms: linear and nonlinear identification techniques for analysis of cardiovascular regulation.
Philos Transact A Math Phys Eng Sci. 2009; 367(1892): 1377-1391. Doi: 10.1098/rsta.2008.0266 [OPEN ACCESS]
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Leading authors Med Uni Graz
Batzel Jerry
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Abstract:
Cardiovascular (CV) regulation is the result of a number of very complex control interactions. As computational power increases and new methods for collecting experimental data emerge, the potential for exploring these interactions through modelling increases as does the potential for clinical application of such models. Understanding these interactions requires the application of a diverse set of modelling techniques. Several recent mathematical modelling techniques will be described in this review paper. Starting from Granger's causality, the problem of closed-loop identification is recalled. The main aspects of linear identification and of grey-box modelling tailored to CV regulation analysis are summarized as well as basic concepts and trends for nonlinear extensions. Sensitivity analysis is presented and discussed as a potent tool for model validation and refinement. The integration of methods and models is fostered for a further physiological comprehension and for the development of more potent and robust diagnostic tools.
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Least-Squares Analysis -
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Sensitivity and Specificity -
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Find related publications in this database (Keywords)
modelling
closed-loop control
closed-loop identification
nonlinear identification
sensitivity analysis
cardiovascular system
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