A bond graph model of the cardiovascular system
V Le Rolle1, A I Hernandez, P Y Richard
1Laboratoire de Traitement du Signal et de l'Image, Inserm U642, Université de Rennes 1 - Campus de Beaulieu, 35042, Rennes Cedex, France.
Insights
This study introduces a new computational model for the cardiovascular system (CVS) and autonomic nervous system (ANS) regulation. The model aids in analyzing complex cardiovascular data from autonomic tests, improving risk stratification for cardiovascular diseases.
Area of Science:
- Physiology
- Biomedical Engineering
- Computational Modeling
Background:
- Autonomic nervous system (ANS) function provides key indicators for cardiovascular disease risk and early detection.
- Analyzing ANS data is challenging due to the complex autonomic regulation of the cardiovascular system (CVS).
- Existing models for ANS-CVS interaction are limited in scope.
Purpose of the Study:
- To present a novel, integrated model of the cardiovascular system (CVS) and its regulation by the autonomic nervous system (ANS).
- To facilitate the analysis of complex cardiovascular data from autonomic function tests.
Main Methods:
- Developed models for vascular system and ventricular activity using Bond Graph formalism for integrated energetic representation.
- Integrated an electrophysiologic model of cardiac action potential using ordinary differential equations.
- Represented short-term ANS regulation (heart rate, contractility, vasoconstriction) using continuous transfer functions.
- Coupled multi-formalism models using a simulation library.
Main Results:
- Successfully simulated cardiovascular responses during Tilt Test and Valsalva Manoeuvre.
- Validated the model by comparing simulated signals with real data from autonomic tests.
- Demonstrated the model's capability to represent electro-mechanical and regulatory aspects of the CVS.
Conclusions:
- The proposed multi-formalism model effectively captures the complex interactions within the cardiovascular system and its autonomic regulation.
- This integrated modeling approach offers a promising tool for analyzing autonomic function test data.
- The model can enhance risk stratification and early detection of cardiovascular pathologies.
Abstract:
The study of the autonomic nervous system (ANS) function has shown to provide useful indicators for risk stratification and early detection on a variety of cardiovascular pathologies. However, data gathered during different tests of the ANS are difficult to analyse, mainly due to the complex mechanisms involved in the autonomic regulation of the cardiovascular system (CVS). Although model-based analysis of ANS data has been already proposed as a way to cope with this complexity, only a few models coupling the main elements involved have been presented in the literature. In this paper, a new model of the CVS, representing the ventricles, the circulatory system and the regulation of the CVS activity by the ANS, is presented. The models of the vascular system and the ventricular activity have been developed using the Bond Graph formalism, as it proposes a unified representation for all energetic domains, facilitating the integration of mechanic and hydraulic phenomena. In order to take into account the electro-mechanical behaviour of both ventricles, an electrophysiologic model of the cardiac action potential, represented by a set of ordinary differential equations, has been integrated. The short-term ANS regulation of heart rate, cardiac contractility and peripheral vasoconstriction is represented by means of continuous transfer functions. These models, represented in different continuous formalisms, are coupled by using a multi-formalism simulation library. Results are presented for two different autonomic tests, namely the Tilt Test and the Valsalva Manoeuvre, by comparing real and simulated signals.
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