DocumentCode :
1225462
Title :
Artificial Odor Discrimination System Using Electronic Nose and Neural Networks for the Identification of Urinary Tract Infection
Author :
Kodogiannis, Vassilis S. ; Lygouras, John N. ; Tarczynski, Andrzej ; Chowdrey, Hardial S.
Author_Institution :
Centre for Syst. Anal., Univ. of Westminster, London
Volume :
12
Issue :
6
fYear :
2008
Firstpage :
707
Lastpage :
713
Abstract :
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 U.K. Public Health Registry. These samples were analyzed by incubation in a volatile generation test tube system for 4-5 h. Two issues are being addressed, including the implementation of an advanced neural network, based on a modified expectation maximization 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 contaminants in urine samples using electronic nose technology.
Keywords :
biochemistry; chemical analysis; diseases; expectation-maximisation algorithm; medical computing; medical signal detection; microorganisms; neural nets; patient diagnosis; pattern recognition; somatosensory phenomena; UK Public Health Registry; artificial odor discrimination; dynamic structure methodology; electronic nose technology; expectation maximization scheme; gas sensing technology; microbial contaminants; neural networks; pattern recognition method; test tube system; time 4 hr to 5 hr; urinary tract infection; Electronic nose; Neural networks; electronic nose; microbial analysis; multiple classifiers; neural networks (NNs); Algorithms; Artificial Intelligence; Diagnostic Techniques, Urological; Electronics, Medical; Fuzzy Logic; Humans; Neural Networks (Computer); Odors; Point-of-Care Systems; Robotics; Smell; Urinary Tract Infections; Urine; Volatile Organic Compounds;
fLanguage :
English
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
Publisher :
ieee
ISSN :
1089-7771
Type :
jour
DOI :
10.1109/TITB.2008.917928
Filename :
4526692
Link To Document :
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