164 results for Hann, C.E.

  • Rocket Roll Dynamics and Disturbance – Minimal modelling and system identification

    Hann, C.E.; Snowdon, M.; Rao, A.; Tang, R.; Korevaar, A.; Skinner, G.; Keall, A.; Chen, X.Q.; Chase, J.G. (2010)


    University of Canterbury Library

    The roll dynamics of a 5kg, 1.3 m high sounding rocket are analyzed in a vertical wind tunnel. Significant turbulence in the tunnel makes the system identification of the effective inertia, damping and asymmetry with respect to roll challenging. A novel method is developed which decouples the disturbance from the rocket frame’s intrinsic roll dynamics and allows accurate prediction of roll rate and angle. The parameter identification method is integral-based, and treats wind disturbances as equivalent to a movement in the actuator fins. The method is robust, requires minimal computation, and gave a realistic disturbance distribution reflecting the randomness of the turbulent wind flow. The mean absolute roll rate of the rocket frame observed in experiments was 16.4 degree/s and the model predicted the roll rate with a median error of 0.51 degrees/s with a 90th percentile of 1.25 degrees/s. The roll angle (measured by an encoder), was tracked by the model with a median absolute error of 0.25 degrees and a 90th percentile of 0.50 degrees. These results prove the concept of this minimal modeling approach which will be extended to pitch and yaw dynamics in the future.

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  • Modeled Insulin Sensitivity and Interstitial Insulin Action from a Pilot Study of Dynamic Insulin Sensitivity Tests

    Lin, J.; Jamaludin, U.; Docherty, P.D.; Razak, N.N.; Le Compte, A.J.; Pretty, C.G.; Hann, C.E.; Shaw, G.M.; Chase, J.G. (2010)


    University of Canterbury Library

    An accurate test for insulin resistance can delay or prevent the development of Type 2 diabetes and its complications. The current gold standard test, CLAMP, is too labor intensive to be used in general practice. A recently developed dynamic insulin sensitivity test, DIST, uses a glucose-insulin-C-peptide model to calculate model-based insulin sensitivity, SI. Preliminary results show good correlation to CLAMP. However both CLAMP and DIST ignore saturation in insulin-mediated glucose removal. This study uses the data from 17 patients who underwent multiple DISTs to investigate interstitial insulin action and its influence on modeled insulin sensitivity. The critical parameters influencing interstitial insulin action are saturation in insulin receptor binding, αG, and plasma-interstitial difiusion rate, nI . Very low values of αG and very low values of nI produced the most intra-patient variability in SI. Repeatability in SI is enhanced with modeled insulin receptor saturation. Future parameter study on subjects with varying degree of insulin resistance may provide a better understanding of different contributing factors of insulin resistance.

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  • Evaluation of the Performances and Costs of a Spectrum of DIST Protocols

    Docherty, P.D.; Chase, J.G.; Lotz, T.F.; Hann, C.E.; TeMorenaga, L.; McAuley, K.A.; Shaw, G.M.; Berkeley, J.E,; Mann, J.I. (2010)


    University of Canterbury Library

    The strategic design of most insulin sensitivity (SI) tests maximises either accuracy or economy, but not both. Hence, accurate, large-scale screening isn’t feasible. The DIST was developed to better optimize both important metrics. The highly flexible DIST protocol samples insulin, glucose and C-peptide during a comparatively short test. Varying the sampling periods and assays, and utilising alternative computational methods enables a wide range of tests with different accuracy and economy tradeoffs. The result is a hierarchy of tests to facilitate low-cost screening. Eight variations of the DIST are evaluated against the fully-sampled test by correlating the SI and endogenous insulin production (Uen(t)) metrics. Five variations include sample and assay reductions and three utilise DISTq parameter estimations. The DISTq identification methods only require glucose assays and thus enable real-time analysis. Three DISTq methods were tested; the fully-sampled, the Short, and the 30 minute two-sample protocol. 218 DIST tests were completed on 84 participants to provide the data for this study. Methods that assayed insulin replicated the findings of the full DIST particularly well (R=0.89~0.92) while those that assayed C-peptide managed to best replicate endogenous insulin metrics (R=0.72~1.0). The three DISTq protocols correlated to the fully-sampled DIST at R=0.83, 0.77 and 0.71 respectively. As expected, test resolution increased with rising protocol cost and intensity. The ability of significantly less expensive tests to replicate the values of the fully-sampled DIST was relatively high (R=0.92 with four glucose and two insulin assays and 0.71 with only two glucose assays). Thus, an SI screening programme could achieve high resolution at a low cost by using a lower resolution DIST test. When an individual’s result is close to a diagnostic threshold stored test samples could be re-assayed for more species to allow a higher resolution analysis without the need for a second invasive clinical test. Hence, a single test can lead to several outcomes with this hierarchy approach, enabling large scale screening with high resolution only where required with minimal and feasible economic cost and only a single invasive clinical procedure.

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  • Intensive Control Insulin-Nutrition-Glucose Model Validated in Critically Ill Patients

    Lin, J.; Razak, N.N.; Pretty, C.G.; LeCompte, A.J.; Docherty, P.D.; Parente, J.D.; Shaw, G.M.; Hann, C.E.; Chase, J.G. (2010)


    University of Canterbury Library

    A comprehensive, more physiologically relevant Intensive Control Insulin-Nutrition- Glucose (ICING) Model is presented and validated using data from critically ill patients. Glucose utilisation and its endogenous production in particular, are more distinctly expressed. A more robust glucose absorption model through ingestion is also added. Finally, this model also includes explicit pathways of insulin kinetics, clearance and utilisation. Identification of critical constant population parameters is carried out parametrically, optimising one hour forward prediction errors, while avoiding model identifiability issues. The identified population values are pG = 0.006 min-1, EGPb = 1.16 mmol/min and nI = 0.003 min-1, all of which are within reported physiological ranges. Insulin sensitivity, SI , is identified hourly for each individual. All other model parameters are kept at well-known population values or functions of body weight or surface area. A sensitivity study confirms the validity of limiting time-varying parameters to SI only. The model achieves median fitting error <1% in data from 173 patients (N = 42,941 hrs in total) who received insulin while in the Intensive Care Unit (ICU) and stayed for more than 72 hrs. Most importantly, the median per patient one-hour ahead prediction error is a very low 2.80% [IQR 1.18, 6.41%]. It is significant that the 75th percentile prediction error is now within the lower bound of typical glucometer measurement errors of 7-12%. This result further confirms that the model is suitable for developing model-based insulin therapies, and capable of delivering tight blood glucose control, in a real-time model based control framework with a tight prediction error range.

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  • A 2 parameter model of lung mechanics to predict volume response and optimise ventilator therapy in ARDS

    Sundaresan, A.; Hann, C.E.; Chase, J.G.; Yuta, T.; Shaw, G.M. (2009)

    Conference Contributions - Other
    University of Canterbury Library

    A majority of patients admitted to the Intensive Care Unit (ICU) require some form of respiratory support. In the case of Acute Respiratory Distress Syndrome (ARDS), the patient often requires full intervention from a mechanical ventilator. ARDS is also associated with mortality rates as high as 70%. Despite many recent studies on ventilator treatment of the disease, there are no well established methods to determine the optimal Positive End expiratory Pressure (PEEP) ventilator setting for individual patients [1]. A model of fundamental lung mechanics is developed based on capturing the recruitment status of lung units. The model produces good correlation with clinical data, and is clinically applicable due to the minimal number of patient specific parameters to identify. The ability to use this identified patient specific model to optimize ventilator management and lung volume recruitment is demonstrated. It thus provides a platform for continuous monitoring of lung unit recruitment and capability for a patient.

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  • Modelling and system identification of a stiff stay wire fence machine

    Hann, C.E.; Aitchison, D.; Kirk, D.; Brouwers, E. (2010)

    Journal Articles
    University of Canterbury Library

    This paper investigates a severe gear backlash problem encountered in a stiff stay machine that is capable of producing a 26 line fence up to 2.6 metres in height at a speed of 80 stays/minute. Related problems in the literature, typically concentrate on the effect of gear backlash on the ability to control a shaft. However, in this case, very good control of the reference speed of the shaft was maintained in spite of the gear backlash. The problem was that the commanded torques were excessively large and threatened to damage the gear box. This problem motivated a complete analysis of the systems dynamics including the development of a model to better understand the response and allow the identification of external loads on the system. It was found that the method of sensing the shaft position (resolvers) was a major factor as well as the upgrading of the motor which was over responding to disturbances in the shaft. The model was validated using several torque limiting experiments and gave accurate prediction of the machine’s major dynamics. The simulation tool developed provides the basis to predict the effect of different loads, wire types and/or motors on the machine for future designs minimizing the amount of experimentation on the machine.

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  • Unique parameter identification for cardiac diagnosis in critical care using minimal data sets

    Hann, C.E.; Chase, J.G.; Desaive, T.; Froissart, C.B.; Revie, J.; Stevenson, D.; Lambermont, B.; Ghuysen, A.; Kolh, P.; Shaw, G.M. (2010)

    Journal Articles
    University of Canterbury Library

    Lumped parameter approaches for modelling the cardiovascular system typically havemany parameters of which a significant percentage are often not identifiable from limited data sets. Hence, significant parts of the model are required to be simulated with little overall effect on the accuracy of data fitting, as well as dramatically increasing the complexity of parameter identification. This separates sub-structures of more complex cardiovascular system models to create uniquely identifiable simplified models that are one to one with the measurements. In addition, a new concept of parameter identification is presented where the changes in the parameters are treated as an actuation force into a feed back control system, and the reference output is taken to be steady state values of measured volume and pressure. The major advantage of the method is that when it converges, it must be at the global minimum so that the solution that best fits the data is always found. By utilizing continuous information from the arterial/pulmonary pressurewaveforms and the end-diastolic time, it is shown that potentially, the ventricle volume is not required in the data set, which was a requirement in earlier published work. The simplified models can also act as a bridge to identifying more sophisticated cardiac models, by providing an initial set of patient specific parameters that can reveal trends and interactions in the data over time. The goal is to apply the simplified models to retrospective data on groups of patients to help characterize population trends or un-modelled dynamics within known bounds. These trends can assist in improved prediction of patient responses to cardiac disturbance and therapy intervention with potentially smaller and less invasive data sets. In this way a more complex model that takes into account individual patient variation can be developed, and applied to the improvement of cardiovascular management in critical care.

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  • A fast generalizable solution method for glucose control algorithms

    Hann, C.E.; Docherty, P.; Chase, J.G.; Shaw, G.M. (2010)

    Journal Articles
    University of Canterbury Library

    In critical care tight control of blood glucose levels has been shown to lead to better clinical outcomes. The need to develop new protocols for tight glucose control, as well as the opportunity to optimize a variety of other drug therapies, has led to resurgence in model-based medical decision support in this area. One still valid hindrance to developing new model-based protocols using so-called virtual patients, retrospective clinical data, and Monte Carlo methods is the large amount of computational time and resources needed. This paper develops fast analytical-based methods for insulin–glucose system model that are generalizable to other similar systems. Exploiting the structure and partial solutions in a subset of the model is the key in finding accurate fast solutions to the full model. This approach successfully reduced computing time by factors of 5600–144000 depending on the numerical error management method, for large (50– 164 patients) virtual trials and Monte Carlo analysis. It thus allows new model-based or model-derived protocols to be rapidly developed via extensive simulation. The new method is rigorously compared to existing standard numerical solutions and is found to be highly accurate to within 0.2%.

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  • Subject-specific cardiovascular system model-based identification and diagnosis of septic shock with a minimally invasive data set: Animal experiments and proof of concept

    Chase, J.G.; Lambermont, B.; Starfinger, C.; Hann, C.E.; Shaw, G.M.; Ghuysen, A.; Kolh, P.; Dauby, P.C.; Desaive, T. (2011)

    Journal Articles
    University of Canterbury Library

    A cardiovascular system (CVS) model and parameter identification method have previously been validated for identifying different cardiac and circulatory dysfunctions in simulation and using porcine models of pulmonary embolism, hypovolemia with PEEP titrations, and induced endotoxic shock. However, these studies required both left and right heart catheters to collect the data required for subject-specific monitoring and diagnosis – a maximally invasive data set in a critical care setting although it does occur in practice. Hence, use of this model-based diagnostic would require significant additional invasive sensors for some subjects, which is unacceptable in some, if not all, cases. The main goal of this study is to prove the concept of using only measurements from one side of the heart (right) in a “minimal” data set to identify an effective patient-specific model that can capture key clinical trends in endotoxic shock. This research extends existing methods to a reduced and minimal data set requiring only a single catheter and reducing the risk of infection and other complications – a very common, typical situation in critical care patients, particularly after cardiac surgery. The extended methods and assumptions that found it are developed and presented in a case study for the patient-specific parameter identification of pig-specific parameters in an animal model of induced endotoxic shock. This case study is used to define the impact of this minimal data set on the quality and accuracy of the model-application for monitoring, detecting and diagnosing septic shock. Six anesthetized healthy pigs weighing 20-30 kg received a 0.5- mg/kg endotoxin infusion over a period of 30 mins from T0 to T30. For this research, only right heart measurements were obtained. Errors for the identified model are within 8% when the model is identified from data, re-simulated and then compared to the experimentally measured data, including measurements not used in the identification process for validation. Importantly, all identified parameter trends match physiologically and clinically and experimentally expected changes, indicating that no diagnostic power is lost. This work represents a further with human subjects validation for this model-based approach to cardiovascular diagnosis and therapy guidance in monitoring endotoxic disease states. The results and methods obtained can be readily extended from this case study to the other animal model results presented previously. Overall, these results provide further support for prospective, proof of concept clinical testing with humans.

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  • Cardiac output estimation using pulmonary mechanics in mechanically ventilated patients

    Sundaresan, A.; Chase, J.G.; Hann, C.E.; Shaw, G.M. (2010)

    Journal Articles
    University of Canterbury Library

    The application of positive end expiratory pressure (PEEP) in mechanically ventilated (MV) patients with acute respiratory distress syndrome (ARDS) decreases cardiac output (CO). Accurate measurement of CO is highly invasive and is not ideal for all MV critically ill patients. However, the link between the PEEP used in MV, and CO provides an opportunity to assess CO via MV therapy and other existing measurements, creating a CO measure without further invasiveness. This paper examines combining models of diffusion resistance and lung mechanics, to help predict CO changes due to PEEP. The CO estimator uses an initial measurement of pulmonary shunt, and estimations of shunt changes due to PEEP to predict CO at different levels of PEEP. Inputs to the cardiac model are the PV loops from the ventilator, as well as the oxygen saturation values using known respiratory inspired oxygen content. The outputs are estimates of pulmonary shunt and CO changes due to changes in applied PEEP. Data from two published studies are used to assess and initially validate this model. The model shows the effect on oxygenation due to decreased CO and decreased shunt, resulting from increased PEEP. It concludes that there is a trade off on oxygenation parameters. More clinically importantly, the model also examines how the rate of CO drop with increased PEEP can be used as a method to determine optimal PEEP, which may be used to optimise MV therapy with respect to the gas exchange achieved, as well as accounting for the impact on the cardiovascular system and its management.

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  • The identification of insulin saturation effects during the Dynamic Insulin Sensitivity Test

    Docherty, P.D.; Chase, J.G.; Hann, C.E.; Lotz, T.F.; Lin, J.; McAuley, K.A.; Shaw, G.M. (2010)

    Journal Articles
    University of Canterbury Library

    Background: Many insulin sensitivity (SI) tests identify a sensitivity metric that is proportional to the total available insulin and measured glucose disposal despite general acceptance that insulin action is saturable. Accounting for insulin action saturation may aid inter-participant and/or inter-test comparisons of insulin efficiency, and model-based glycaemic regulation. Method: Eighteen subjects participated in 46 dynamic insulin sensitivity tests (DIST, low-dose 40-50 minute insulinmodified IVGTT). The data was used to identify and compare SI metrics from three models: a proportional model (SIL), a saturable model (SIS and Q50) and a model similar to the Minimal Model (SG and SIG). The three models are compared using inter-trial parameter repeatability, and fit to data. Results: The single variable proportional model produced the metric with least intra-subject variation: 13.8% vs 40.1%/55.6%, (SIS/I50) for the saturable model and 15.8%/88.2% (SIG/SG) for the third model. The average plasma insulin concentration at half maximum action (I50) was 139.3 mU·L-1, which is comparable to studies which use more robust stepped EIC protocols. Conclusions: The saturation model and method presented enables a reasonable estimation of an overall patient-specific saturation threshold, which is a unique result for a test of such low dose and duration. The detection of previously published population trends and significant bias above noise suggests that the model and method successfully detects actual saturation signals. Furthermore, the saturation model allowed closer fits to the clinical data than the other models, and the saturation parameter showed a moderate distinction between NGT and IFG-T2DM subgroups. However, the proposed model did not provide metrics of sufficient resolution to enable confidence in the method for either SI metric comparisons across dynamic tests or for glycamic control.

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  • Investigating the Applicability of qALPV Modeling to ICU Models for Glycaemic Control

    Kovacs, L.; Gyorgy, A.; Szalay, P.; Benyo, B.; Benyo, Z.; Hann, C.E.; Chase, J.G. (2010)

    Conference Contributions - Published
    University of Canterbury Library

    Maintenance of glucose levels in intensive care unit (ICU) patients via control of insulin inputs is currently an active research field. Different published models that address this problem are analysed from control theory point of view. This paper analyzes the three most used ICU metabolic system models in the literature, two of which have been validated in clinical trials or alternate clinical use. Global control theoretical characteristics are determined using nonlinear analysis. Quasi affine linear parameter varying (qALPV) modeling methodology is then investigated for further robust nonlinear model based control.

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  • Mitral valve dynamics in a closed-loop model of the cardiovascular system

    Desaive, T.; Paeme, S.; Chase, J.G.; Hann, C.E.; Lambermont, B.; Kolh, P.; Moonen, M.; Lancellotti, P.; Dauby, P.C.; Barnett, A. (2009)

    Conference Contributions - Other
    University of Canterbury Library

    Introduction: A cardiovascular and circulatory system (CVS) model has been validated in silico, and in several animal model studies. It accounts for valve dynamics by means of Heaviside function to simulate “open on pressure, close on flow” law. Thus, it does not consider the real time scale of the valve aperture and thus doesn’t fully capture valve dysfunction. This research couples the CVS model with a model describing the progressive aperture of the mitral valve. Method: We used a CVS system model with 6 elastic chambers (left and right ventricles, vena cava, aorta, pulmonary artery and veins) also accounting for ventricular interaction by means of septum displacement. The mitral valve aperture was modelled by considering the pressure forces induced by blood flow during a complete cardiac cycle. This valve equation was coupled with the CVS model to simulate cardiac hemodynamics with healthy and diseased regurgitating valves. Results: We compared the simulations with the initial CVS model and the Heaviside valve law and with the new model including variable mitral valve aperture. Hemodynamics variables trends in both models show a good correlation and the new model describes accurately the opening and closing of the valve as expected physiologically. Despite the large number of parameters to optimise, we simulated realistically mitral valve regurgitation and found pressure-volume loops comparable to those observed clinically. Conclusions: This work describes a new coupled model of the cardiovascular system that accounts for progressive mitral valve aperture. Simulations show good correlation with physiologically expected results for healthy or diseased valves. The large number of valve model parameters indicates a need for emerging, lighter and minimal mitral valve models that are readily identifiable to achieve full benefit in real-time use. These results suggest a further use of this model to track, diagnose and control valves pathologies.

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  • Model-based Cardiovascular Therapeutics: Capturing the patient-specific impact of inotrope therapy

    Desaive, T.; Starfinger, C.; Chase, J.G.; Hann, C.E.; Shaw, G.M. (2009)

    Conference Contributions - Other
    University of Canterbury Library

    Introduction: A model for the cardiovascular and circulatory systems (CVS) has previously been validated in silico, as well as in porcine models of pulmonary embolism (PE), septic shock, and positive end-expiratory pressure (PEEP) titrations at different volemic levels. An accurate CVS system model can be used to monitor and diagnose dysfunction and support clinical decisions. This research validates this model with respect to inotrope therapy commonly used in circulatory support, prior to first human clinical trials. Method: The model and parameter identification process is used to study the effect of different adrenaline doses in healthy and critically ill patients. The hemodynamic effects on arterial blood pressures and stroke volume (cardiac index) are simulated in the model and adrenaline-specific parameters identified. These parameters are then used to capture and predict the future responses to a change in dose and-or over time. Results are compared to clinical data from 3 adrenaline published dosing studies, comprising a total of N=37 data sets. Results: All identified parameter trends match clinically expected changes. The adrenaline-specific parameters are physiologically relevant. Absolute percentage errors for the patient-specific, predicted hemodynamic responses (N=15) are within 10% compared to clinical data. The adrenaline-specific parameters accurately and uniquely capture the impact of inotrope therapy on the CVS, independent of other model parameters. Conclusions: Clinically accurate prediction of the impact of circulatory support drugs, such as adrenaline, offers significant clinical potential for this type of model-based application. Overall, this work represents a further clinical validation of the underlying fundamental CVS model and methods, and their use for cardiovascular diagnosis and therapy selection in critical care. These results are presented as (further) justification for (beginning) human trials of this model-based diagnostic and therapeutic approach.

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  • Tight Glycemic Control - The Leading Role of Insulin Sensitivity in Determining Efficacy and Thus Outcome

    Chase, J.G.; LeCompte, A.J.; Shaw, G.M.; Lin, J.; Pretty, C.G.; Razak, N.; Parente, J.; Lynn, A.; Hann, C.E.; Suhaimi, F. (2009)

    Conference Contributions - Published
    University of Canterbury Library

    invited keynote/plenary paper and talk

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  • Algorithmic Processing of Pressure Waveforms to Facilitate Estimation of Cardiac Elastance

    Stevenson, D.; Revie, J.A.; Chase, J.G.; Hann, C.E.; Shaw, G.M.; Lambermont, B.; Ghuysen, A.; Kolh, P.; Desaive, T. (2012)

    Journal Articles
    University of Canterbury Library

    Background: Cardiac elastances are highly invasive to measure directly, but are clinically useful due to the amount of information embedded in them. Information about the cardiac elastance, which can be used to estimate it, can be found in the downstream pressure waveforms of the aortic pressure (Pao) and the pulmonary artery (Ppa). However these pressure waveforms are typically noisy and biased, and require processing in order to locate the specific information required for cardiac elastance estimations. This paper presents the method to algorithmically process the pressure waveforms. Methods: A shear transform is developed in order to help locate information in the pressure waveforms. This transform turns difficult to locate corners into easy to locate maximum or minimum points as well as providing error correction. Results: The method located all points on 87 out of 88 waveforms for Ppa, to within the sampling frequency. For Pao, out of 616 total points, 605 were found within 1%, 5 within 5%, 4 within 10% and 2 within 20%. Conclusions: The presented method provides a robust, accurate and dysfunction-independent way to locate points on the aortic and pulmonary artery pressure waveforms, allowing the non-invasive estimation of the left and right cardiacelastance.

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  • Structural model of the mitral valve included in a cardiovascular closed-loop model: Static and dynamic validation

    Paeme, S.; Moorhead, K.; Chase, J.G.; Lambermont, B.; Kolh, P.; Lancellotti, P.; Dauby, P.C.; Desaive, T.; Hann, C.E.; Moonen, M. (2012)

    Conference Contributions - Published
    University of Canterbury Library

    invited, 6-pages

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  • A simplified model for mitral valve dynamics

    Moorhead, K.T.; Paeme, S.; Chase, J.G.; Kolh, P.; Pierard, L.; Hann, C.E.; Dauby, P.C.; Desaive, T. (2013)

    Journal Articles
    University of Canterbury Library

    Located between the left atrium and the left ventricle, the mitral valve controls flow between these two cardiac chambers. Mitral valve dysfunction is a major cause of cardiac dysfunction and its dynamics are little known. A simple non-linear rotational spring model is developed and implemented to capture the dynamics of the mitral valve. A measured pressure difference curve was used as the input into the model, which represents an applied torque to the anatomical valve chords. A range of mechanical model hysteresis states were investigated to find a model that best matches reported animal data of chord movement during a heartbeat. The study is limited by the use of one dataset from the literature. However, results clearly highlight some physiological issues, such as the damping and chord stiffness changing within one cardiac cycle. Very good correlation was achieved between modeled and experimental valve angle with 1-10% absolute error in the best case, indicating good promise for future simulation of cardiac valvular dysfunction, such as mitral regurgitation or stenosis. In particular, the model provides a pathway to capturing these dysfunctions in terms of modeled stiffness or elastance that can be directly related to anatomical, structural defects and dysfunction.

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  • A Subcutaneous Insulin Pharmacokinetic Model for Computer Simulation in a Diabetes Decision Support Role: Validation and Simulation

    Chase, J.G.; Hann, C.E.; Shaw, G.M.; Lotz, T.F.; Lin, J.; Le Compte, A.J.; Wong, J. (2008)

    Journal Articles
    University of Canterbury Library

    Companion paper #2

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  • A Low-Cost Unmanned Underwater Vehicle Prototype for Shallow Water Tasks

    Wang, W.H.; Chen, X.Q.; Marburg, A.; Chase, J.G.; Hann, C.E. (2008)

    Conference Contributions - Published
    University of Canterbury Library

    Unmanned underwater vehicles (UUVs) have received worldwide attention and been widely used in various applications. In this paper, a recently developed low cost UUV prototype at the University of Canterbury is introduced, which is designed specifically for shallow water tasks, especially for inspecting and cleaning sea chests of ships for biosecurity purpose. The main hull of the UUV is made of PVC, with a 400mm diameter and 800mm length. External frames mount two horizontal propellers, four vertical thrusters, and power is sea chest derived from onboard batteries. The maximum thrust force of up to 10kg that is provided by the propellers can generate a forward/backward speed of up to 1.4mIs for the 112kg UUV. The vertical thrusters provide depth control with a max thrust force of 20kg. The UUV is equipped with a range of sensors capable of sensing its instantaneous temperature, depth, attitude and surrounding environment. Costing less than US$10,000 for a prototype, it provides an excellent platform for further underwater vehicle development targeting shallow water tasks with a working depth up to 20m.

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