| EPSRC Reference: |
GR/N14200/01 |
| Title: |
PATTERN RECOGNITION AND CLASSIFICATION OF VF ECG TRACES BY A COMBINED NEURAL NETWORK-STATISTICS METHOD |
| Principal Investigator: |
Lu, Dr W |
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| Department: |
Physics |
| Organisation: |
Heriot-Watt University |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 September 2000 |
Ends: |
30 November 2001 |
Value (£): |
44,070
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| EPSRC Research Topic Classifications: |
| Intelligent & Expert Systems |
Med.Instrument.Device& Equip. |
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Summary on Grant Application Form |
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Experiments and modelling of animal hearts have shown complex yet structured and ordered patterns of propagation are sustainable in ventricles and they may underlie VF. These exciting discoveries provide impetus for new approaches to the diagnosis and treatment of VF. This pilot project aims to study pattern recognition and classification of clinical ECG traces during VF using robust heteroscedastic probabilistic neural networks in combination with statistical analysis. It is a timely response to the Foresight Steering Group's initiative on Progress Through Partnership and Winning Through Foresight. The novelty of this investigation is in the innovative artificial neural network methodology and in the strategy of a combined ANNs and statistical analysis approach to pattern recognition and classification of complex data sets.The project will develop and strengthen collaborations among the partners within the newly formed Edinburgh Multidisciplinary Consortium for Advanced Nonlinear Analysis of Complex Systems, core-funded by the Scottish Higher Education Funding Council in 1998. Dr. C. E. Robertson, a consultant from the Royal Infirmary of Edinburgh, is a member of the Consortium and the main collaborator in this project.
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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 |
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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.hw.ac.uk |