Kodogiannis, Vassilis and Lygouras, John N. and Tarczynski, Andrzej and Chowdrey, Hardial S. (2008) Artificial Odor Discrimination System using electronic nose and neural networks for the identification of urinary tract infection. IEEE Transactions on Information Technology in Biomedicine, 12 (6). pp. 707-713. ISSN 1089-7771
Official URL: http://dx.doi.org/10.1109/TITB.2008.917928
Current clinical diagnostics are based on biochemical, immunological or microbiological methods. However, these methods are operator dependent, time consuming, expensive and require special skills, and are therefore not suitable for point-of-care testing. Recent developments in gas-sensing technology and pattern recognition methods make electronic nose technology an interesting alternative for medical point-of-care devices. An electronic nose has been used to detect Urinary Tract Infection from 45 suspected cases that were sent for analysis in a UK Public Health Registry. These samples were analysed by incubation in a volatile generation test tube system for 4-5h. Two issues are being addressed, including the implementation of an advanced neural network, based on a modified Expectation Maximisation scheme that incorporates a dynamic structure methodology and the concept of a fusion of multiple classifiers dedicated to specific feature parameters. This study has shown the potential for early detection of microbial ontaminants in urine samples using electronic nose technology.
|Research Community:||University of Westminster > Electronics and Computer Science, School of|
University of Westminster > Life Sciences, School of
|Deposited On:||24 Jun 2008 15:28|
|Last Modified:||11 Aug 2010 15:33|
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