| EPSRC Reference: |
EP/F057016/1 |
| Title: |
PREVENTING VENTILATOR-ASSOCIATED LUNG INJURY USING FEEDBACK CONTROL ENGINEERING |
| Principal Investigator: |
Bates, Professor D |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Engineering |
| Organisation: |
University of Leicester |
| Scheme: |
Standard Research |
| Starts: |
06 October 2008 |
Ends: |
28 February 2010 |
Value (£): |
200,932
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| EPSRC Research Topic Classifications: |
| Control Engineering |
Medical science & disease |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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13 Feb 2008
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System Approaches to Well Being Panel
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Announced
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Summary on Grant Application Form |
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This project will develop a multi-compartmental, multi-scalar, mathematical model of alveolar ventilation dynamics (which includes gas exchange, dynamic and non-linear alveolar compliance and bronchial resistance), cardiovascular performance and blood (with reference to its gas-carrying abilities). The developed model will be used to elucidate the extent and distribution of the factors causative of lung injury in diseased, heterogeneous, mechanically-ventilated lungs. By treating the problem as one of feedback control, we will investigate methods of parameter adjustment in the mechanical ventilator to optimise cardiac output and arterial gas tensions while minimising the factors associated with VALI. Due to the inevitable complexity of the simulation model which we intend to develop, advanced methods from multivariable robust and optimal control theory will be required in order to identify which combinations of parameters should be adjusted, and how, in order to achieve the desired reduction in VALI. The work will go beyond that previously attempted in quantifying the factors that risk lung injury during mechanical ventilation through the greater fidelity of the proposed simulation platform. In addition, we will apply robustness analysis techniques to the modelling to improve the reliability and applicability of our findings. This will allow us to perform population modelling, rather than the commonly used approach of modelling and studying a single, idealized subject, rendering our findings applicable to populations and to a variety of real patients, in contrast to previous work where the idealized subject is in fact representative of neither the population nor any one individual.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.le.ac.uk |