Julie Fontecave-Jallon

Integration of detailed modules in a core model of body fluid homeostasis and blood pressure regulation

This paper presents a contribution to the definition of the interfaces required to perform heterogeneous model integration in the context of integrative physiology. A formalization of the model integration problem is proposed and a coupling method is presented. The extension of the classic Guyton model, a multi-organ, integrated systems model of blood pressure regulation, is used as an example of the application of the proposed method. To this end, the Guyton model has been restructured, extensive sensitivity analyses have been performed, and appropriate transformations have been applied to replace a subset of its constituting modules by integrating a pulsatile heart and an updated representation of the renin-angiotensin system. Simulation results of the extended integrated model are presented and the impacts of their integration within the original model are evaluated.

A Wearable Technology Revisited for Cardio-Respiratory Functional Exploration: Stroke Volume Estimation from Respiratory Inductive Plethysmography

The objective of the present study is to extract new information from complex signals generated by Respiratory Inductive Plethysmography (RIP). This indirect cardio-respiratory (CR) measure is a well-known wearable solution. The authors applied time-scale analysis to estimate cardiac activity from thoracic volume variations, witnesses of CR interactions. Calibrated RIP signals gathered from 4 healthy volunteers in resting conditions are processed by Ensemble Empirical Mode Decomposition to extract cardiac volume signals and estimate stroke volumes. Averaged values of these stroke volumes (SVRIP) are compared with averaged values of stroke volumes determined simultaneously by electrical impedance cardiography (SVICG). There is a satisfactory correlation between SVRIP and SVICG (r=0.76, p

Modeling quasi-periodic signals by a non-parametric model: Application on fetal ECG extraction

Quasi-periodic signals can be modeled by their second order statistics as Gaussian process. This work presents a non-parametric method to model such signals. ECG, as a quasi-periodic signal, can also be modeled by such method which can help to extract the fetal ECG from the maternal ECG signal, using a single source abdominal channel. The prior information on the signal shape, and on the maternal and fetal RR interval, helps to better estimate the parameters while applying the Bayesian principles. The values of the parameters of the method, among which the R-peak instants, are accurately estimated using the Metropolis-Hastings algorithm. This estimation provides very precise values for the R-peaks, so that they can be located even between the existing time samples.

Implementation of a Model of Bodily Fluids Regulation

Abstract The classic model of blood pressure regulation by Guyton et al. (Annu Rev Physiol 34:13–46, 1972a; Ann Biomed Eng 1:254–281, 1972b) set a new standard for quantitative exploration of physiological function and led to important new insights, some of which still remain the focus of debate, such as whether the kidney plays the primary role in the genesis of hypertension (Montani et al. in Exp Physiol 24:41–54, 2009a; Exp Physiol 94:382–388, 2009b; Osborn et al. in Exp Physiol 94:389–396, 2009a; Exp Physiol 94:388–389, 2009b). Key to the success of this model was the fact that the authors made the computer code (in FORTRAN) freely available and eventually provided a convivial user interface for exploration of model behavior on early microcomputers (Montani et al. in Int J Bio-med Comput 24:41–54, 1989). Ikeda et al. (Ann Biomed Eng 7:135–166, 1979) developed an offshoot of the Guyton model targeting especially the regulation of body fluids and acid–base balance; their model provides extended renal and respiratory functions and would be a good basis for further extensions. In the interest of providing a simple, useable version of Ikeda et al.’s model and to facilitate further such extensions, we present a practical implementation of the model of Ikeda et al. (Ann Biomed Eng 7:135–166, 1979), using the ODE solver Berkeley Madonna.

Probabilistic model definition for physiological state monitoring

Assessing the global situation of a person from physiological data is a well-known difficult problem. In previous work, we propose a system that does not produce a diagnosis but instead follows a set of hypotheses and decides of an alarming situation with this information. In this paper we focus on data processing part of the system taking into account the complexity and the ambiguity of the data. We propose a statistical approach with a global model based on Hidden Markov Model and we present data models that rely on classical physiological parameters and experts knowledge. We then learn a model that depends on the person and its environment, and we define and compute confidence values to assess the plausibility of hypotheses.

Towards a suitable time-scale representation of cardio-respiratory signals through Empirical Mode Decomposition algorithms: A simulation and validation tool

To what extent is Empirical Mode Decomposition (EMD) able to differentiate the embedded components of a cardio-respiratory (CR) signal? We intend to answer this question by providing a tool which compares the performances of the original EMD algorithm with those of a noise-assisted version (CEEMD) on simulated CR signals, depending on the frequency and amplitude ratios between their respiratory and cardiac components. A statistical Bland & Altman test checks the matching of stroke volumes calculated from the extracted cardiac signal and those from the simulated one. CEEMD turns out to be better than EMD by yielding to reliable multiscale representation of simulated CR signals on a wider domain of frequency and amplitude ratios.

A simple mathematical model of spontaneous swallow effects on breathing based on new experimental data

The coordination of respiration and swallowing involves an interaction between two central pattern generators, and this can be disturbed in some pathological situations. To better understand this interaction, we aim in this study to characterize the effect of a spontaneous swallow on the breathing pattern. This is first realized using Respiratory Inductive Plethysmography on 11 healthy subjects. Real signals highlight several mechanisms for swallowing: ending of inspiration, prolongation of expiration or active expiration. These behaviours have been integrated in an existing model of the respiratory system simulating the activity of the respiratory centers, the respiratory muscles, and rib cage internal mechanics. The resulting model of interaction between breathing and swallowing is compatible with the observed effects and is driven for swallowing by a limited number of parameters.The coordination of respiration and swallowing involves an interaction between two central pattern generators, and this can be disturbed in some pathological situations. To better understand this interaction, we aim in this study to characterize the effect of a spontaneous swallow on the breathing pattern. This is first realized using Respiratory Inductive Plethysmography on 11 healthy subjects. Real signals highlight several mechanisms for swallowing: ending of inspiration, prolongation of expiration or active expiration. These behaviours have been integrated in an existing model of the respiratory system simulating the activity of the respiratory centers, the respiratory muscles, and rib cage internal mechanics. The resulting model of interaction between breathing and swallowing is compatible with the observed effects and is driven for swallowing by a limited number of parameters.

Non-invasive cardiac output monitoring in pharmacology: A plethysmographie solution in rats

Cardiovascular monitoring is of great importance in pharmacology but there is a lack of convenient non-invasive alternatives. Hence, we aim to evaluate the relevance of inductive plethysmography (IP) in preclinical cardiac studies. An IP system was specifically designed for rat. Its evaluation carried out using a mechanical test bench has shown appropriate instrumental performances for cardiac monitoring in rats. Measurements were also performed during a volume overload hemodynamic challenge in vivo in rats. The cardiac output variation has similar kinetic and amplitude when compared to results of previous studies. This suggests that our system is suitable for cardiac output monitoring in rat.

Empirical Mode Decomposition of Respiratory Inductive Plethysmographic signals for stroke volume variations monitoring: Respiratory protocol and comparison with impedance cardiography

We investigate Respiratory Inductive Plethysmography (RIP) to estimate cardiac activity from thoracic volume variations and study cardio-respiratory interactions. The objective of the present study is to evaluate the ability of RIP to monitor stroke volume (SV) variations, with reference to impedance cardiography (IMP). Five healthy volunteers in seated and supine positions were asked to blow into a manometer in order to induce significant SV decreases. Time-scale analysis was applied on calibrated RIP signals to extract cardiac volume signals. Averaged SV values, in quasi-stationary states at rest and during the respiratory maneuvers, were then estimated from these cardiac signals and from IMP signals simultaneously acquired. SV variations between rest and maneuvers were finally evaluated for both techniques. We show that SV values as well as SV variations are correlated between RIP and IMP estimations, suggesting that RIP could be used for SV variations monitoring.

Proceedings of the XXIXth Conference of the French-Speaking Society for Theoretical Biology

The papers comprising the present issue deal with quantitative and qualitative approaches in life science. They form an issue focused on formalisms, models and simulations in biology and health which has its roots in the congress on the same topic held by the French-speaking Society for Theoretical Biology (SFBT) from 14 to 17 June 2009 in Saint-Flour (France). Indeed, the central role of modelling and simulation in systems analysis of biological and physiological systems is now clearly established. Emerging disciplines, such as Systems Biology, and research programs at the international level, such as the IUPS Physiome, or European level, such as the ‘‘Virtual Physiological Human’’ (VPH), are well defined and rely extensively on methods and tools for modelling and simulation in the fields of biology and biomedical research. The SFBT was created in the early 80s with the objective to promote the development of methods and theoretical formalisms useful for understanding fundamental biological concepts as well as for biological research and practical application. At the present time, this society turns rather into mathematical biology. The strength and the originality of this society are to bring together scientists from various formations and with heterogeneous backgrounds for debating around hot topics in mathematical biology. These cross-disciplinary connections often raise interesting and fruitful discussions, and sometimes give birth to new collaborations. For most of the participants, the SFBT meeting, which takes place once a year in St Flour (France) and once every three years in a French-speaking country (Canada, Morocco), is the place where they can exchange new ideas and discover new theoretical works in mathematical biology.