Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/70787
Title: A novel medical E-nose signal analysis system
Authors: Kou, L 
Zhang, D 
Liu, DX
Issue Date: 2017
Source: Sensors, Apr. 2017, v. 17, no. 4, 402, p. 1-15
Abstract: It has been proven that certain biomarkers in people's breath have a relationship with diseases and blood glucose levels (BGLs). As a result, it is possible to detect diseases and predict BGLs by analysis of breath samples captured by e-noses. In this paper, a novel optimized medical e-nose system specified for disease diagnosis and BGL prediction is proposed. A large-scale breath dataset has been collected using the proposed system. Experiments have been organized on the collected dataset and the experimental results have shown that the proposed system can well solve the problems of existing systems. The methods have effectively improved the classification accuracy.
Keywords: E-nose
Chemical sensors
Breath analysis
Blood glucose level
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sensors 
ISSN: 1424-8220
DOI: 10.3390/s17040402
Rights: © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
The following publication Kou, L., Zhang, D., & Liu, D. X. (2017). A novel medical E-nose signal analysis system. Sensors, 17(4), (Suppl. ), 402, - is available athttps://dx.doi.org/10.3390/s17040402
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