A Novel Medical E-Nose Signal Analysis System

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 s...

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Detalles Bibliográficos
Autores principales: Kou, Lu, Zhang, David, Liu, Dongxu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5419773/
https://www.ncbi.nlm.nih.gov/pubmed/28379168
http://dx.doi.org/10.3390/s17040402
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author Kou, Lu
Zhang, David
Liu, Dongxu
author_facet Kou, Lu
Zhang, David
Liu, Dongxu
author_sort Kou, Lu
collection PubMed
description 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.
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spelling pubmed-54197732017-05-12 A Novel Medical E-Nose Signal Analysis System Kou, Lu Zhang, David Liu, Dongxu Sensors (Basel) Article 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. MDPI 2017-04-05 /pmc/articles/PMC5419773/ /pubmed/28379168 http://dx.doi.org/10.3390/s17040402 Text en © 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/).
spellingShingle Article
Kou, Lu
Zhang, David
Liu, Dongxu
A Novel Medical E-Nose Signal Analysis System
title A Novel Medical E-Nose Signal Analysis System
title_full A Novel Medical E-Nose Signal Analysis System
title_fullStr A Novel Medical E-Nose Signal Analysis System
title_full_unstemmed A Novel Medical E-Nose Signal Analysis System
title_short A Novel Medical E-Nose Signal Analysis System
title_sort novel medical e-nose signal analysis system
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5419773/
https://www.ncbi.nlm.nih.gov/pubmed/28379168
http://dx.doi.org/10.3390/s17040402
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