Control Systems and Modelling - Research Groups -The Centre for Bioengineering - University of Canterbury - New Zealand

Control Systems and Modelling to Assist ICU Patients

Cardiovascular Systems Modelling and Model-Based Diagnosis

Professor Chase is the leader of this research area if you wish to receive more information

This project uses models of the cardiovascular system (CVS). We are modeling and system identifying a complex heart and circulation model for use in critical care for advanced diagnosis and therapy decision support using measurements from catheters and sensors already commonly used in critically ill patients - i.e. no added cost or technology required.

These models are applied to sort a wealth of clincal data and develop patient specific diagnoses from otherwise limited and confusing data, which entails using the stream of numbers that are output to identify model parameters. Identified model parameters thus take this data and create a picture of the physiological system status for the patient. The outcome is thus a patient specific model on which different treatments can be applied/tested to optimise therapy.

We are just entering a more clinically oriented phase that will see a mix of modeling and clinical development. Prior to this we have done extensive animal trials to validate the system with partners at the University of Liege in Belgium. 

This area also has some need for mechatronics oriented research work developing better data gathering systems and methods, as well as real-time data analysis if that is an area of interest.

ARDS Lung Mechanics for Optimizing Ventilator Treatment

Professor Chase is the leader of this research area if you wish to receive more information

This project develops model of mechanics of passively breathing lung, as in case of an Acute Respiratory Distress Syndrome (ARDS) patient under mechanical ventilation. The model is based on simplified physiology of actual lungs and it uses relatively new concept, where the majority of volume change occurs by recruitment and collapse of alveoli units. The model captures the dynamic characteristics of lungs through Unit Compliance Curve and Threshold Opening and Closing Pressure of lung units. The ultimate goal of this project is to develop a model based decision-support tool for clinical situation, where the model simulates the patient and condition specific lung from a few clinical data and determine the updated optimal setting for the ventilator.

Modelling and Control of the Insulin-Glucose Metabolic System to control Hyperglycemia in Intensive Care and Diabetes Mellitus patients

Professor Chase is the leader of this research area if you wish to receive more information

Diabetes is a widespread problem reaching epidemic proportions around the world. The high blood glucose concentrations, or hyperglycaemia, resulting from Diabetes is a cause for further complications and a higher mortality risk for the affected patients. Intensive care patients are often hyperglycaemic due to the stress of their condition. A tight control of blood glucose in this population has shown to drastically reduce their mortality rate.

The body utilizes insulin to remove glucose from the blood plasma. However, patients with hyperglycaemia have an impaired endogenous insulin metabolism, which can not cope with the task of supplying the right amount of insulin to maintain a normal range of blood glucose concentration. Inter- and intra-individual variability in insulin sensitivity, as well as variability in patient condition, makes it very difficult to find a general, one-size-fits-most solution to the highly nonlinear problem of optimizing insulin dosing and glycaemic control.

This project deals with

  • Automating the monitoring and dosing of insulin for intensive care and diabetes patients, and applying advanced modelling and adaptive control design for the automation of insulin infusion. This area includes theoretical work in simulating and optimizing the trial protocols as well as practical implementation of these in proof of concept clinical trials.
  • Improving current models to improve the predictive ability of the system and account for greater physiological variations and effects.
  • Implementation of emerging continuous glucose sensors into closed loop systems to reduce human interaction. Problems arising due to sensor lag and errors have to be dealt with by applying appropriate filtering and control techniques.
  • Development of a low-intensity model-based test to quantify of insulin resistance for the broad population, focusing on clinical practicability and higher accuracy than current methods.

 

This multi-disciplinary project is carried out in cooperation with the following institutionsClinical control protocol

  • The Christchurch Hospital ICU
  • The Department of Mathematics and Statistics
  • The Edgar National Centre for Diabetes Research, Dunedin, NZ
  • The Lipids and Diabetes Research Group at Christchurch Hospital

Initial proof-of concept clinical trails are carried out in the Christchurch Hospital ICU. The current control protocol involves constant monitoring of patient blood glucose levels and reviewing of patient-specific parameters that govern the blood glucose variability. Through theses step thus the insulin requirement can be determined and administered.

Sedation-Agitation Sensor for Intubated Patients in the ICU

Professor Chase is the leader of this research area if you wish to receive more information

ICU patientIntensive care unit (ICU) patients are often intubated to help them breathe, and sedated to minimize pain and agitation from the intubation as well as other injuries. Patients that are not sedated enough often become agitated and try to remove the breathing tube causing distress and anxiety that are difficult to control without unnecessary extra sedation.

The goal of this project is to

  • Create a sensor array to measure patient motion with existing sensor technology
  • Correlate and quantify patient motion to existing qualitative agitation scales

The basic premise is that patient motion, and other metrics, are directly correlated to patient agitation. Current measures of patient agitation are qualitative relying on medical staff to make periodic, subjective judgments.The application of modern sensor and signal processing technology presents the opportunity to gather more data and apply it to create a qualitative, far more precise, determination of patient agitation. Success would enable better sedation-agitation modelling as well as a more quantified approach to controlling sedation processes. This project is run in conjunction with Dr. Geoff Shaw, M.D. a research anesthesiologistwith the Christchurch Hospital and the Otago School of Medicine.

Modelling and Control of the Sedation-Agitation Curve in ICU Patients

Professor Chase is the leader of this research area if you wish to receive more information

Intensive care unit (ICU) patients that are not sedated enough often become agitated and try to remove the breathing tube causing distress and anxiety that are difficult to control without extra sedation. Conversely, over, or heavily, sedated patients take significantly longer returning to a conscious state, adding significant cost and time to their hospital stay as well as additional risk due to over sedation.

Ventillator checkerThe primary problem is twofold

  • Lack of an adequate model relating agitation and sedation
  • Inability of shrinking nursing staffs to consistently understand, dose and treat sedated patients with the minimum necessary sedation, i.e. lack of automatic control

This project looks at addressing these two problems. The first part creates a quantifiable sedation-agitation model suitable to covering the majority of patient behaviours in terms of relating sedative concentration to qualitative level of sedation and a quantified level of measured agitation. The second part examines applying control systems technology to this system to obtain more robust and consistent results, and to achieve more minimal levels of sedation to minimize ICU stays and healthcare cost. This project is also run in conjunction with Dr. Geoff Shaw, M.D. a research anesthesiologist with the Christchurch Hospital and the Otago School of Medicine.

  • The Centre for Bioengineering
    University of Canterbury
    Private Bag 4800, Christchurch
    New Zealand
  • Phone +64 3 364 2987 ext 43210
    bioeng@canterbury.ac.nz
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