DocumentCode
792243
Title
Medical diagnosis with the gradient microarray of the KAMINA
Author
Koronczi, Ilona ; Ziegler, Karlheinz ; Krüger, Uwe ; Goschnick, Joachim
Author_Institution
Inst. fur Instrumentelle Analytik, Forschungszentrum Karlsruhe, Germany
Volume
2
Issue
3
fYear
2002
fDate
6/1/2002 12:00:00 AM
Firstpage
254
Lastpage
259
Abstract
Investigations with human breath and cultures of oral bacteria have been performed to examine the analytical performance of the KAMINA gradient microarray based on a segmented metal oxide layer. Standard microarray chips with 38 segments, one chip equipped with platinum doped SnO2 and the other with WO3, were inspected. The results show that the gradient microarray is able to detect acetone and methyl-mercaptane as two model gases of medical relevance at lower ppm-levels in the presence of human breath. Even after consumption of smelly nutrition, acetone at lowest concentrations of some 10 ppm could be detected. A principal component analysis (PCA) of the signal patterns showed that both types of microarrays were able to discriminate between the model gases, ethanol and clean air. Moreover, the even more delicate distinction of different oral bacteria grown on an agar substrate proved to be feasible by the signal pattern analysis of their gaseous metabolites. The signal patterns obtained for mixed bacteria cultures even seem to allow assignment to and quantification of the main cultures of a mixture.
Keywords
chemical analysis; gas sensors; microorganisms; microsensors; organic compounds; patient diagnosis; platinum; tin compounds; tungsten compounds; KAMINA gradient microarray; SnO2:Pt; WO3; acetone; agar substrate; bacteria discrimination; clean air; e-nose; ethanol; gradient microarray; human breath; medical diagnosis; methyl-mercaptane; oral bacteria; principal component analysis; segmented metal oxide layer; signal pattern analysis; Ethanol; Gases; Humans; Medical diagnosis; Medical diagnostic imaging; Microorganisms; Pattern analysis; Performance analysis; Platinum; Principal component analysis;
fLanguage
English
Journal_Title
Sensors Journal, IEEE
Publisher
ieee
ISSN
1530-437X
Type
jour
DOI
10.1109/JSEN.2002.800288
Filename
1021066
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