References of "Stevenson, D"
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See detailAlgorithmic Processing of Pressure Waveforms to FacilitateEstimation of Cardiac Elastance
Stevenson, D.; Revie, J.; Chase, J. G. et al

in BioMedical Engineering OnLine (2012), 11

Introduction: Cardiac elastances are highly invasive to measure directly, but are clinically useful due tothe amount of information embedded in them. Information about the cardiac elastance, which can be ... [more ▼]

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

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See detailComputer-based monitoring of global cardiovascular dynamics during acute pulmonary embolism and septic shock in swine
Revie, JA; Stevenson, D; Chase, JG et al

in Critical Care (2012), 16 (Suppl 1)

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See detailEstimating afterload, systemic vascular resistance and pulmonary vascular resistance in an intensive care setting
Stevenson, D; Revie, J.; Chase, JG et al

in Proceedings of BMS2012 (2012)

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See detailModel-based Monitoring of Septic Shock Treated with Large-Pore Hemofiltration Therapy
Revie; Stevenson, D; Chase, JG et al

in Proceedings of BMS 2012 (2012)

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See detailAnalysis of Aortic Energetics from Pulse Wave Examination in a Porcine Study of Septic Shock
Revie, JA; Stevenson, D; Chase, JG et al

in Prceedings of BMS 2012 (2012)

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See detailPatient specific identification of the cardiac driver function in a cardiovascular system model.
Hann, C. E.; Revie, J.; Stevenson, D. et al

in Computer Methods & Programs in Biomedicine (2011)

The cardiac muscle activation or driver function, is a major determinant of cardiovascular dynamics, and is often approximated by the ratio of the left ventricle pressure to the left ventricle volume. In ... [more ▼]

The cardiac muscle activation or driver function, is a major determinant of cardiovascular dynamics, and is often approximated by the ratio of the left ventricle pressure to the left ventricle volume. In an intensive care unit, the left ventricle pressure is usually never measured, and the left ventricle volume is only measured occasionally by echocardiography, so is not available real-time. This paper develops a method for identifying the driver function based on correlates with geometrical features in the aortic pressure waveform. The method is included in an overall cardiovascular modelling approach, and is clinically validated on a porcine model of pulmonary embolism. For validation a comparison is done between the optimized parameters for a baseline model, which uses the direct measurements of the left ventricle pressure and volume, and the optimized parameters from the approximated driver function. The parameters do not significantly change between the two approaches thus showing that the patient specific approach to identifying the driver function is valid, and has potential clinically. [less ▲]

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See detailDiagnosing pulmonary embolism from a model-based cardiac driver function
Stevenson, D; Revie, JA; Chase, JG et al

in Proceedings of ANZICS 2011 (2011)

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See detailProcessing aortic and pulmonary artery waveforms to derive the ventricle time-varying elastance
Stevenson, D; Chase, JG; Hann, CE et al

in Proceedings of the 18th IFAC World Congress, 2011 (2011)

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See detailModel-based diagnosis of acute pulmonary embolism and septic shock in porcine trials
Revie, JA; Stevenson, D; Chase, JG et al

in Proceedings of the Health Research Society of Christchurch Annual Scientific Session 2011 (2011)

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See detailPatient specific modelling of cardiac muscle activation
Stevenson, D; Hann, CE; Revie, JA et al

in Proceedings of the Health Research Society of Canterbury (HRSC) Clinical Meeting 2010 (2010)

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See detailModel-based cardiac disease diagnosis in critical care
Revie, JA; Hann, CE; Stevenson, D et al

in Proceedings of the Health Research Society of Canterbury (HRSC) Clinical Meeting 2010 (2010)

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See detailEstimating the driver function of a cardiovascular system model
Stevenson, D; Hann, CE; Chase, JG et al

in Proceedings of CONTROL 2010 (2010)

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See detailA Model-based Approach to Cardiovascular Monitoring of Pulmonary Embolism
Revie, JA; Hann, CE; Stevenson, D et al

in Proceedings of CONTROL 2010 (2010)

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See detailPatient-specific modelling of cardiovascular dysfunction: Identifying models of pulmonary embolism in pigs
Desaive, Thomas ULg; Revie, J; Hann, CE et al

in Proceedings of the 19th International Conference of the Cardiovascular System Dynamics Society (2010)

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See detailTime varying elastance estimation in an 8 camber cardiovascular system model
Desaive, Thomas ULg; Chase, J. G.; Hann, C. E. et al

in Intensive Care Medicine (2010), 36(2), 151-151

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See detailUnique parameter identification for cardiac diagnosis in critical care using minimal data sets.
Hann, C. E.; Chase, J. G.; Desaive, Thomas ULg et al

in Computer Methods & Programs in Biomedicine (2010)

Lumped parameter approaches for modelling the cardiovascular system typically have many parameters of which a significant percentage are often not identifiable from limited data sets. Hence, significant ... [more ▼]

Lumped parameter approaches for modelling the cardiovascular system typically have many 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 pressure waveforms 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. [less ▲]

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See detailModel-based prediction of the patient-specific response to adrenaline
Chase, J. G.; Starfinger, C.; Hann, C. E. et al

in The open medical informatics journal (2010), 4

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See detailUnique parameter identification of a cardiovascular system model using feedback control
Hann, C. E.; Chase, J. G.; Desaive, Thomas ULg et al

in Proc. 7th Intl Conf on Control and Automation (ICCA09) (2009, December)

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See detailUnique parameter identification for model-based cardiac diagnosis in critical care
Hann, C. E.; Chase, J. G.; Desaive, Thomas ULg et al

in IFAC Proceedings Volumes (IFAC-PapersOnline) (2009), 7(PART 1), 169-174

Lumped parameter approaches for modeling the cardiovascular system typically have many parameters of which many are not identifiable. The conventional approach is to only identify a small subset of ... [more ▼]

Lumped parameter approaches for modeling the cardiovascular system typically have many parameters of which many are not identifiable. The conventional approach is to only identify a small subset of parameters to match measured data, and to set the remaining parameters at population values. These values are often based on animal data or the "average human" response. The problem, is that setting many parameters at nominal fixed values, may introduce dynamics that are not present in a specific patient. As parameter numbers and model complexity increase, more clinical data is required for validation and the model limitations are harder to quantify. This paper considers the modeling and the parameter identification simultaneously, and creates models that are one to one with the measurements. That is, every input parameter into the model is uniquely optimized to capture the clinical data and no parameters are set at population values. The result is a geometrical characterization of a previously developed six chamber heart model, and a completely patient specific approach to cardiac diagnosis in critical care. In addition, simplified sub-structures of the six chamber model are created to provide very fast and accurate parameter identification from arbitrary starting points and with no prior knowledge on the parameters. Furthermore, by utilizing continuous information from the arterial/pulmonary pressure waveforms and the end-diastolic time, it is shown that only the stroke volumes of the ventricles are required for adequate cardiac diagnosis. This reduced data set is more practical for an intensive care unit as the maximum and minimum volumes are no longer needed, which was a requirement in prior work. The simplified models can also act as a bridge to identifying more sophisticated cardiac models, by providing a generating set of waveforms that the complex models can match to. Most importantly, this approach does not have any predefined assumptions on patient dynamics other than the basic model structure, and is thus suitable for improving cardiovascular management in critical care by optimizing therapy for individual patients. © 2009 IFAC. [less ▲]

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See detailRobust parameter identification for model-based cardiac diagnosis in critical care
Hann, C. E.; Chase, J. C.; Desaive, Thomas ULg et al

in Proceedings of the 6th IFAC Symposium on Modeling and Control in Biomedical Systems (MCBMS09) (2009)

Detailed reference viewed: 14 (4 ULg)