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Open AccessArticle

A Novel Medical E-Nose Signal Analysis System

by Lu Kou 1, David Zhang 1,2,* and Dongxu Liu 2
Biometrics Research Center, Department of Computing, The Hong Kong Polytechnic University, Kowloon 999077, Hong Kong, China
Department of Computer Science, Harbin Institute of Technology Shenzhen graduate school, Shenzhen 518055, China
Author to whom correspondence should be addressed.
Academic Editors: Woosuck Shin and Toshio Itoh
Sensors 2017, 17(4), 402;
Received: 31 October 2016 / Revised: 4 February 2017 / Accepted: 16 February 2017 / Published: 5 April 2017
(This article belongs to the Special Issue Gas Sensors for Health Care and Medical Applications)
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. View Full-Text
Keywords: e-nose; chemical sensors; breath analysis; blood glucose level e-nose; chemical sensors; breath analysis; blood glucose level
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Kou, L.; Zhang, D.; Liu, D. A Novel Medical E-Nose Signal Analysis System. Sensors 2017, 17, 402.

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