Authors: McLoone, Violeta, Ringwood, John V., Van Vliet, Bruce

Abstract: Salt-induced hypertension has been widely studied in rats, monkeys, chimpanzees and humans. Until recently, the multiple phases of this blood pressure increase due to high salt intake had not been closely studied. This work builds upon a recent study, which developed a grey-box multi-component model of salt-induced hypertension in the Dahl-S rat. The previous 3-component model has been extended here to include additional model dynamics to improve the model fit and add new important elements to the model response. The model was optimised using numerical techniques with experimental data from 4 different protocols with Dahl-S and hybrid rats. Results show a marked improvement over the previous model and confirm the merit of the 5-component model structure.

Keywords: Biomedical signal processing; Circulatory and respiratory systems; Bioinformatics

Identifier: 10.3182/20090812-3-DK-2006.00030

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Gøtzsche, Mette, Nielsen, Stinne Klitgaard, Rees, Stephen Edward

Abstract: Control of respiration has previously been investigated, and models have been built to explain dierent aspects of respiration. Models of respiratory drive have been limited in terms of the description of acid-base relations in blood. The purpose of this study is to explore the consequences of adding an acid-base model of the whole body to a respiratory drive model. We built a model that combines a compartment model of acid-base relations of the whole body, and a model of respiratory drive. We explored which effect the buffering capacity of full blood compared to only plasma has on respiratory drive, and we investigated which consequences the addition of body compartments has on the dynamic behavior of the model. The addition of a whole blood model results in only small differences in respiratory drive over the physiological range. Adding compartment volumes for blood, tissue and interstitial fuid results in a changed dynamic behavior when the system is exposed to a typical physiological change. In conclusion, it is not necessary to include the buffering capacity of whole blood compared to plasma in a model of this kind. A compartment model seems to give a better understanding of the dynamics of change in respiration.

Keywords: Circulatory and respiratory systems

Identifier: 10.3182/20090812-3-DK-2006.00043

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Barceló-Rico, Fátima, Díez, José Luis

Abstract: This paper compares dierent proposals for codifying categorical attributes in a Heart Disease database, in order to be able to apply numerical clustering algorithms to them. The main idea of the new approach is a codification of categorical attributes based on polar coordinates. This will be compared with other methods for clustering mixed databases found in literature. This proposal has many advantages: it relatively easy to understand and apply, the increment in the length of the input matrix is not excessively large, and the committed error is under control. The proposed codification has been combined in this case with the well known K-means algorithm and has showed a very good performance in a Heart Disease database benchmark.

Keywords: Biomedical signal processing

Identifier: 10.3182/20090812-3-DK-2006.00028

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Mogensen, Mads Lause, Steimle, Kristoffer Lindegaard, Karbing, Dan Stieper, Andreassen, Steen

Abstract: This study presents a stratified model that simulates the pulmonary capillary blood flow under influence of different lung volumes. The model includes capillary geometry, capillary wall elasticity, pressure exerted by the heart, blood viscosity, the erect of the chest wall and hydrostatic effects of the lung tissue and of the blood. The model simulates highly pulsatile blood flow with a heterogenous flow distribution down the lungs, in agreement with previous experimental studies. Moreover the model is in agreement with experimentally measured total capillary flow, total capillary volume, total capillary surface area and transition time of red blood cells passing through the pulmonary capillary network. The presented model is the first to describe the link between lung volume and perfusion.

Keywords: Circulatory and respiratory systems; Control of physiological and clinical variables,; Decision support and control of biomedical systems

Identifier: 10.3182/20090812-3-DK-2006.00027

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Steimle, Kristoffer Lindegaard, Mogensen, Mads Lause, Karbing, Dan Stieper, Bernardino de la Serna, Jorge, Smith, Bram W, Vacek, Ondrej, Andreassen, Steen

Abstract: This paper presents a model of the lung mechanics and simulates the pulmonary alveolar ventilation. The model includes the alveolar geometry and distribution and pressures exerted by the chest wall, due to surface tension affected by surfactant activity, due to lung tissue elasticity and due to the hydrostatic effects of the lung tissue and blood utilizing a stratified subdivision of the lungs. The model simulates a heterogenous ventilation distribution down the lungs in agreement with experimental studies. Furthermore the model is in agreement with experimentally measured hysteresis, static lung compliance, lung volumes and density distribution at different lung volumes. The presented model is the first to simulate alveolar ventilation including all of the above mentioned components of the respiratory system.

Keywords: Circulatory and respiratory systems; Control of voluntary movements, respiration,; Critical care and decision support systems

Identifier: 10.3182/20090812-3-DK-2006.00038

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Kariv, Galia, Shani, Vered, Goldberg, Elad, Leibovici, Leonard, Paul, Mical

Abstract: Background: Opportunistic pulmonary infections are a major cause of morbidity and mortality among solid organ transplant recipients. The diagnosis of these infections is challenging because of the broad spectrum of bacteria, fungi and viruses affecting these patients. Treatment directed at the offending organism started as soon as possible improves survival. Objective: To develop a decision support system for the diagnosis of pulmonary infections in solid-organ transplant recipients. The model's goal is to improve the accuracy of the diagnosis and thus the appropriateness of empirical treatment. Design: The model is built using a Bayesian network (also known as Causal Probabilistic Network). The network is based on pathogen segments which are the main building blocks of the model. All segments share common risk factors, such as time after transplantation, latent infections of donor/ recipient and organ transplanted. The segments are linked at symptoms, signs and diagnostic tests common to all pathogens. The outputs of the model are predicted probabilities of infectious pathogens. To populate the model with data we have mainly abstracted data from the literature, using a systematic approach. The structure of the model and its adaptation for decision support will be presented. Evaluation: The first evaluation phase assessed the model's diagnosis in a series of 20 representative cases of opportunistic infections. A match between the case’s diagnosis and the model’s prediction was achieved in 17/20 of cases. The next evaluation phase will consist of a prospective observational study comparing the accuracy of the model's diagnosis vs. that of the physician within 24 hours of episode onset, as compared with a gold-standard diagnosis ascribed to the patients at the end of the infectious episode by two independent experts. Data for this phase are currently collected prospectively.

Keywords: Cellular and molecular systems

Identifier: 10.3182/20090812-3-DK-2006.00060

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Watson, Edmund, Chappell, Michael, Ducrozet, Frederic, Poucher, Simon Martin, Yates, James

Abstract: The glucose-insulin system is a challenging process to model due to the feedback mechanisms present, hence the implementation of a model-based approach to the system is an on-going and challenging research area. A new approach is proposed here which provides an effective way of characterising glycaemic regulation. The resulting model is built on the premise that there are three phases of insulin secretion, similar to those seen in a proportional- integral-derivative (PID) type controller used in engineering control problems. The model relates these three phases to a biological understanding of the system, as well as the logical premise that the homeostatic mechanisms will maintain very tight control of the system. It includes compartments for insulin, glucose, insulin action and a compartment to simulate an integral function of glucose. Structural identifiability analysis was performed on the model to determine whether a unique set of parameter values could be obtained from the available observations, which would allow meaningful conclusions to be drawn from parameter estimation. Although two parameters - glucose production rate and the proportional control coefficient - were found to be unidentifiable, the former is not a concern as this is known to be impossible to measure without a tracer experiment, and the latter can be easily estimated from other means. Subsequent parameter estimation and the model simulations have shown good agreement with respect to real data.

Keywords: Kinetic modelling and system control; Endocrine and metabolic systems

Identifier: 10.3182/20090812-3-DK-2006.00014

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Szlávecz, Ákos, Benyo, Balazs, Steinbach, Cecilia, Hesz, Gábor, Fördős, Gergely, Bukki, Tamas

Abstract: In this paper we present the development of a modelling convention and a modelling environment, called PetDetSim, able to describe different PET detector block geometries. By the developed simulation environment the PET detector block designer can easily define different detector block configurations and test their optical behaviour regarding the characteristic features defining the imaging quality of the device. Beside the common optical behaviour of the detector block the developed modelling environment is also able to model gamma photon penetration. The PetDetSim environment is designed to use on a computer cluster and in a grid computing environment in order to reduce the computation time of the simulation. The validation of PetDetSim has been successfully done in the case of basic detector models, i.e. consisting of a single crystal needle.

Keywords: Biomedical imaging systems; Functional imaging and data modelling

Identifier: 10.3182/20090812-3-DK-2006.00053

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Guo, Yu, Ruan, Su, Landré, Jérôme, Constans, Jean-Marc

Abstract: Because of the overlapping of the spectra of different metabolites and the interference of the baseline mainly from broad resonances of macromolecule and lipids, it is difficult to achieve the quantification of spectra of different metabolites which is important for both research and clinical applications of Magnetic Resonance Spectroscopy (MRS). In this paper, a novel MRS quantification method based on frequency a priori knowledge is proposed. Firstly, a wavelet filter is used to remove the broad components of an observed spectrum in which baseline and the relatively broad components of metabolite spectrum are included. Secondly, a linear nonnegative pursuit algorithm based on regularized FOCUSS (Focal Underdetermined System Solver) algorithm is used to decompose the filtered spectra in a dictionary which is based on a set of Lorentzian and Gaussian functions corresponding to spectrum models. Benefitting from the a priori knowledge of the peak frequency of each metabolite, the filtered metabolite spectrum can be sparsely represented with these basis functions and the spectra of different metabolites are relevant to certain basis functions. Therefore, with the corresponding relation between the basis functions and spectrum models and the estimated decomposition coefficients, a mixed spectrum without baseline can be reconstructed and spectra of different metabolites can be quantified at the same time. The accuracy and the robustness of MRS quantification are improved by the proposed method, from simulation data, compared with commonly used MRS quantification methods. Quantification on in vivo brain spectra is also demonstrated.

Keywords: Biomedical signal processing; Quantification of physiological parametes for diagnosis assessment

Identifier: 10.3182/20090812-3-DK-2006.00036

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Garcia-Gabin, Winston, Zambrano, Darine, Bondia Company, Jorge, Vehi, Josep

Abstract: The development of robust and efficient glucose control algorithms is key to making the artificial pancreas a reality. In this paper a sliding mode predictive control (SMPC) is obtained by combining the design technique of a sliding mode control with a model based predictive control (MPC). The SMPC combines the main advantages of the two control methods: the robust features of SMC and the good performance of MPC, including the handling of constraints on manipulated and controlled variables. Control action is composed by three parts: a predictive one from an optimization problem, a discontinuous one given by the switching term and finally, a feed-forward action given by an insulin bolus that is injected when a meal is ingested. The prediction model is linear and it is represented by a second order model with time delay. In order to test the controller in silico experiments, the Hovorka model has been considered. The proposed control algorithm shows considerable robustness for intra-patient variability, as well as an enhanced ability to handle measurement uncertainties and disturbance rejection, especially focusing on postprandial behaviour.

Keywords: Control of physiological and clinical variables,; Endocrine and metabolic systems

Identifier: 10.3182/20090812-3-DK-2006.00015

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Zheng, Xiujuan, Wen, Lingfeng, Yu, Shu-Jung, Feng, David Dagan, Huang, Sung-Cheng

Abstract: Plasma time-activity curve (PTAC) is usually required in tracer kinetic modeling as the input function of an underlying kinetic model for quantifying in-vivo pathological/physiological changes. The procedure of invasive arterial blood sampling poses more challenges especially for small animal studies due to limited blood volume and small-size blood vessel. In this study, a recently proposed non-invasive quantification method based on Patlak graphic analysis (PGA) was systematically investigated by using five whole-body dynamic FDG-PET studies of mice. The nonlinear least square (NLS) method and invasive PGA were also used for the comparison. The results demonstrated that the high linearity of relative influx rates was observed between the non-invasive PGA and invasive PGA. Brain is suggested to be reference ROI for non-invasive PGA with slight overestimation of relative influx rate for tumor. The non-invasive PGA approach could be an effective solution in small-animal FDG-PET dynamic studies when the contribution of k4 can be ignored.

Keywords: Kinetic modelling and system control

Identifier: 10.3182/20090812-3-DK-2006.00037

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Szilagyi, Sandor Miklos, Szilagyi, Laszlo, Iclănzan, David Andrei, Benyo, Zoltan

Abstract: This paper presents a patient specific deformable heart model that involves the known electric and mechanic properties of the cardiac cells and tissue. The accuracy and efficiency of the algorithm was tested for anisotropic and inhomogeneous 3D domains using ten Tusscher’s and Nygen’s cardiac cell models. During propagation of depolarization wave, the kinetic, compositional and rotational anisotropy is included in the tissue, organ and torso model. The applied patient specific parameters were determined by an evolutionary computation method. An intensive parameter reduction was performed using the abstract formulation of the searching space. This patient specific parameter representation enables the adjustment of deformable model parameters in real-time. The validation process was performed using measured ECG and ultrasound image records that were compared with simulated signals and shapes using an abstract, parameterized evaluation criterion.

Keywords: Functional imaging and data modelling; Cellular and molecular systems; Biomedical signal processing

Identifier: 10.3182/20090812-3-DK-2006.00047

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Derraz, Foued, Pinti, Antonio

Abstract: Segmentation of tumor from MRI images is difficult task. In fact this due to the large diversity in shape and appearance of tumors regions with intensities overlapping the normal brain tissues. An expanding tumor can also prevent and deform nearby tissue. In this paper, we proposed Active Contour segmentation based method that incorporates histograms of clustered features and appearance priors to separate the tumor from brain tissue. Experimental results on difficult cases have drawn a very good performance of proposed segmentation method Active contour method, Level-set, Clustering methods, Appearance priors, Tumors, F-measure.

Keywords: Biomedical imaging systems; Functional imaging and data modelling

Identifier: 10.3182/20090812-3-DK-2006.00050

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Smieja, Jaroslaw

Abstract: The paper presents advantages and drawbacks of mathematical modeling in building and testing hypotheses concerning structure of regulatory networks. The simulation results clearly show advantages of mathematical modeling. Its application yields good results, in particular in rejection of hypotheses, as it is relatively easy to build and subsequently analyze properties of models of regulatory processes in the pathway. This undoubtedly helps to save resources which would otherwise be devoted to experimental testing of the hypotheses. Through analysis of dynamics of unknown processes, mathematical models can indicate how to find either completely new molecules or unveil new roles of the known ones. Though very helpful in biomedical field, mathematical modeling must be used very carefully and in a supervised mode. When unsupervised automatic methods are applied, they are usually based on minimization of a performance index defined as a squared distance between simulation and experimental data. Such approach can lead to acceptance of models that exhibit dynamical behavior that is qualitatively different from the one observed experimentally.

Keywords: Kinetic modelling and system control; Cellular and molecular systems; Disease control and critical care,

Identifier: 10.3182/20090812-3-DK-2006.00061

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Fang, Chaoqun, Wang, Xiuying, Feng, David Dagan

Abstract: The combination of positron emission tomography (PET) and computed tomography (CT) scanning provides a superior access to both functional information and anatomical structures of the airway tree. However, airway tree segmentation from such low-dose and low-contrast CT images is a challenging task due to the limitation of the image resolutions. Complex anatomical structure of airway tree and partial volume effect pose other difficulties in airway segmentation. Conventional airway segmentation algorithms often produce less than satisfying results. In this paper, we propose a novel method for fully automatic airway tree segmentation for CT images from combined PET/CT scanners. In our method, airway modeling is used in seed extraction and prediction, and a new strategy is devised for identifying potential airway branches that are not detectable by conventional 3D region growing. In comparison with traditional 3D region growing segmentation algorithm, our method outperforms with not only retrieving considerably larger number of branches, but also providing more accurate geometric information.

Keywords: Functional imaging and data modelling; Biomedical imaging systems; Bioinformatics

Identifier: 10.3182/20090812-3-DK-2006.00034

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: dos Santos Ferreira, Jorge, Middleton, Rick

Abstract: A mathematical model is developed to further examine the dynamic interaction of uninfected T cells with Human Immunodeficiency Virus (HIV) mutations. We study how the dynamics are affected by immune response to infected cells under intermittent antiretroviral therapy. Our goal is to analyze the SMART (Strategies for Management of Anti-retroviral Therapy) study outcomes and based on that try to identify possible causes of its failure. We mathematically describe the HIV infection and perform numerical simulation to approach the course of the disease. Preliminary results suggest that the scheduling of follow-up visits and working range of CD4+ T cells count used during the SMART study could explain the observed adverse outcomes in that trial.

Keywords: Decision support and control of biomedical systems; Disease control and critical care,

Identifier: 10.3182/20090812-3-DK-2006.00059

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Pinti, Antonio

Abstract: In the diagnosis using MRI images, image segmentation techniques play a key role. Existing segmentation methods are generally based on the features such as grey level and texture. However, these methods can’t identify the physical significance of segmented objects from image because the general features such as grey level can not take into consideration the specialized medical knowledge, which is important when doctors study them manually using their own vision and experience. To deal with this problem, many tissue classification systems have been developed by incorporating the specific medical knowledge. All of these systems focus on specific applications and are not normalized and structured. So they lack of certainty and precision when being applied in other contexts. In this paper, we propose an intelligent generalized tissue classification system which combines both the Fuzzy C-Means algorithm and the qualitative medical knowledge on geometric properties of different tissues. In this system, a general geometric model is proposed which permits to formalize non structured and non normalized medical knowledge from various medical images. A user friendly interface has been constructed so that medical knowledge can be integrated into this data structure in an interactive way. This system has been successfully applied to the classification of human thigh, crus, arm, forearm, and brain in MRI images

Keywords: Biomedical imaging systems

Identifier: 10.3182/20090812-3-DK-2006.00046

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Wolkewitz, Martin, Schumacher, Martin

Abstract: Mathematical modelling of infectious diseases gains growing attention in epidemiology during the last decades. The major benefits of simulating compartmental models are the prediction of the consequences of potential interventions, a deeper understanding of epidemicdynamics and clinical decision support. The main limitation is however that several parameters are based on uncertain expert guesses (default values) and are not estimated from the study data. In this paper we build a bridge between the well-known deterministic S-I-R (Susceptible-Infectious-Removed) model which can be described with differential equations and the stochastic counterpart which can be used for statistical inference if outbreak data on an individual patient level are available. The possibly time-dependent transmission rate as well as the (basic) reproduction number are the main epidemiological parameters of interest. Furthermore, one important type of heterogeneity is considered: individuals may vary due to their susceptibility, i.e., risk factors for infection may be investigated. The Cox-Aalen survival model that is based on a multiplicative-additive hazard structure turned out to be a suitable tool for that purpose. The results give valuable informations for clinicians working in infection control and public health.

Keywords: Bioinformatics

Identifier: 10.3182/20090812-3-DK-2006.00054

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Patek, Stephen D., Hughes, Colleen, Breton, Marc, Kovatchev, Boris

Abstract: The delay associated with subcutaneous glucose sensing and insulin infusion actuation significantly complicates the design of control algorithms for regulating blood glucose in patients with Type 1 Diabetes Mellitus (T1DM). Model predictive control (MPC) is one strategy for mitigating delay, where optimal insulin infusions can be given in anticipation of future meal disturbances. Unfortunately, exact prior knowledge of meals can only be assured in a clinical environment, and uncertainty about when and if meals will arrive could lead to catastrophic outcomes. In this paper we develop an MPC-like control law that can anticipate meals given a probabilistic description of the patient's eating behavior in the form of a random meal (behavioral) profile. Preclinical in silico trials using the oral glucose meal model of Dalla Man et al. show that the control strategy provides a convenient means to account for uncertain prior knowledge of meals without compromising patient safety, even in the event that anticipated meals are skipped.

Keywords: Endocrine and metabolic systems; Disease control and critical care,; Control of physiological and clinical variables,

Identifier: 10.3182/20090812-3-DK-2006.00007

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Szilagyi, Laszlo, Szilagyi, Sandor Miklos, Benyo, Balazs, Benyo, Zoltan

Abstract: Intensity inhomogeneity or intensity non-uniformity (INU) is an undesired phenomenon that represents the main obstacle for MR image segmentation and registration methods. Various techniques have been proposed to eliminate or compensate the INU, most of which are embedded into clustering algorithms. This paper proposes a hybrid c-means clustering approach to replace the FCM algorithm found in several existing solutions. The novel clustering model is assisted by a pre-filtering technique for Gaussian and impulse noise elimination, and a smoothening filter that helps the c-means algorithm at the estimation of inhomogeneity as a slowly varying additive or multiplicative noise. The slow variance of the estimated INU is assured by a smoothening filter that performs a context dependent averaging, based on a morphological criterion. The experiments using 2-D synthetic phantoms and real MR images show that the proposed method provides more accurate and more efficient segmentation than the FCM based approach. The produced segmentation and fuzzy membership values can serve as excellent support for 3-D registration and segmentation techniques.

Keywords: Biomedical imaging systems; Functional imaging and data modelling; Biomedical signal processing

Identifier: 10.3182/20090812-3-DK-2006.00035

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: None

Abstract:

Keywords:

Identifier: 10.3182/20090812-3-DK-2006.90004

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Dosen, Strahinja, Popovic, Dejan

Abstract: Bipedal walking of humans can be described as a cyclic sequence of synergistic activities of both sensory and motor systems, where sensory systems provide necessary timing and spatial information for potentially required corrections of motor signals (muscle activity). Neural Prosthesis for Walking (NPW) is an assistive system which aims to augment muscle activity; thereby restore walking in individuals with paralysis. The controller for an NPW must provide external activation (i.e., bursts of electrical pulses to motor neurons of paralyzed muscles) which will ensure that the paralyzed extremity follows desired trajectory that is healthy like. The method suggested here is based on the following assumptions: 1) the control should be customized to the musculoskeletal properties of a potential user; and 2) it should mimic the operation of biological control. The method includes four steps: 1) collection of sensor data during walking of a healthy individual and estimation of trajectories in the form suitable for simulation; 2) estimation of muscle activations based on dynamic optimization applied to the model with parameters customized to the potential user; 3) application of classification and regression trees (CARTs) for determination of mapping between the recorded sensor inputs and simulation-determined muscle activities; and 4) transfer of the CART-determined map into a microcontroller which receives data from sensors mounted on the patient and outputs electrical stimulation to the electrodes positioned appropriately on the patient. The first 3 phases are off-line operations implemented on a Windows based host computer, while the last phase operates in real time (portable microcontroller-based stimulator). In the case presented here the sensors are accelerometers and force sensing resistors, and the stimulator supports up to four channels of stimulation. The results of this method were translated into a clinical study for a four-channel NPW assisting training of the walking of hemiplegic individuals.

Keywords: Cellular and molecular systems; Neurosystems; Musculoskeletal systems

Identifier: 10.3182/20090812-3-DK-2006.00063

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Le Compte, Aaron, Chase, J. Geoffrey, Lynn, Adrienne, Hann, Christopher E, Shaw, Geoffrey M, Lin, Jessica

Abstract: Premature neonates often experience hyperglycaemia, which has been linked to increased mortality and worsened outcomes. Insulin therapy can assist in controlling blood glucose levels. However a reliable, robust control protocol is required to avoid hypoglycaemia and to meet nutrition goals. This study presents an adaptive, model-based predictive controller designed to incorporate the unique metabolic state and control parameters of the neonate. Controller performance was tested in virtual trials on a 25 patient retrospective cohort and 24-hour pilot clinical trials. The effects of measurement frequency and BG sensor error were also evaluated. Time in the 4 – 7 mmol/L BG band was increased by 110%-145% compared to retrospective control for that cohort, with fewer hypoglycaemic measurements. Controllers were robust to BG sensor errors.

Keywords: Critical care and decision support systems; Endocrine and metabolic systems; Pharmacokinetics and drug delivery,

Identifier: 10.3182/20090812-3-DK-2006.00004

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Pielmeier, Ulrike, Andreassen, Steen, Steenfeldt Nielsen, Birgitte, Hann, Christopher E, Chase, J. Geoffrey, Haure, Pernille

Abstract: Models of glucose metabolism can help to simulate and predict the blood glucose response in hyperglycaemic, critically ill patients. Model prediction performance depends on a sufficiently accurate estimation of the patient's time-varying insulin sensitivity. The work presents three least squares approaches, the integral method and a Bayesian method that have been compared by prediction accuracy on an absolute and on a relative scale. Clinical data yields 1491 blood glucose predictions based on 10 critically ill patients. The Bayesian approach proved to be best with small errors (9.7% absolute percent error, 14.7 root mean square of logarithmic error for prediction times <= 2h), and fewer and smaller outliers compared to the other methods. Computationally, the Bayesian method took 1.5 times longer per prediction compared to the fastest method. It can be concluded that a Bayesian parameter estimation gives safe and effective results for the insulin sensitivity estimation for this model.

Keywords: Endocrine and metabolic systems; Control of physiological and clinical variables,; Critical care and decision support systems

Identifier: 10.3182/20090812-3-DK-2006.00012

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009

Authors: Grandjean, Thomas R. B., Chappell, Michael, Yates, James, Jones, Kevin, Coleman, Tanya, Wood, Gemma

Abstract: A mathematical model for the pharmacokinetics of Hoechst 33342 following administration into a culture medium containing a population of transfected cells (HEK293 hBCRP) with a potent inhibitor, Fumitremorgin C (FTC), present is described. This non-linear compartmental model has seven macroscopic sub-units, with fourteen rate parameters. A kinetic modelling software package, namely FACSIMILE (MPCA Software, UK), was used to obtain numerical solutions for the system equations and for parameter fitting. Model fits gave good agreement with in-vitro data provided by AstraZeneca.

Keywords: Pharmacokinetics and drug delivery,; Cellular and molecular systems; Kinetic modelling and system control

Identifier: 10.3182/20090812-3-DK-2006.00020

Conference: 7th IFAC Symposium on Modelling and Control in Biomedical Systems

Location: Hvide Hus, Denmark

Start Date: Wed Aug 12 2009 - End Date: Fri Aug 14 2009