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 |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Kou_Medical_E-nose_Signal.pdf | 2.95 MB | Adobe PDF | View/Open |
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