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Title: An effective feature extraction method used in breath analysis
Authors: Chen, H
Lu, G
Guo, D
Zhang, D 
Keywords: Breath odor
Curve fitting
Feature extraction
Issue Date: 2010
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2010, v. 6165 LNCS, p. 33-41 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: It has been reported that human breath could represent some kinds of diseases. By analyzing the components of breath odor, it is easy to detect the diseases the subjects infected. The accuracy of breath analysis depends greatly on what feature are extracted from the response curve of breath analysis system. In this paper, we proposed an effective feature extraction method based on curve fitting for breath analysis, where breath odor were captured and processed by a self-designed breath analysis system. Two parametric analytic models were used to fit the ascending and descending part of the sensor signals respectively, and the set of best-fitting parameters were taken as features. This process is fast, robust, and with less fitting error than other fitting models. Experimental results showed that the features extracted by our method can significantly enhance the performance of subsequent classification algorithms.
Description: 2nd International Conference on Medical Biometrics, ICMB 2010, Hong Kong, 28-30 June 2010
ISBN: 3642139221
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-642-13923-9_4
Appears in Collections:Conference Paper

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