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A Novel Medical E-Nose Signal Analysis System

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Breath Analysis for Medical Applications

Abstract

Some components in human breath have been proven to be associated with certain diseases, such as diabetes and renal disease. The concentration of these components can also be linked to condition status, for example, blood glucose levels (BGLs) . We called these components diseases biomarkers and seek ways to detect them in human breath by using a specially designed e-nose system plus advanced pattern recognition algorithms. In this chapter, a novel optimized medical e-nose system specially for disease diagnosis and BGL prediction is proposed. A large scaled breath dataset is collected by the proposed system. Experiments are conducted on the collected dataset and the experimental results have shown that the proposed system can well solve the problems of existed systems and the methods have effectively improved the classification accuracy.

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Author information

Authors and Affiliations

  1. Biometrics Research Centre, The Hong Kong Polytechnic University, Hong Kong, China

    David Zhang

  2. Wake Forest University, Winston-Salem, NC, USA

    Dongmin Guo

  3. National Institute of Health, Bethesda, USA

    Ke Yan

Authors
  1. David Zhang
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  2. Dongmin Guo
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  3. Ke Yan
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Corresponding author

Correspondence to David Zhang .

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© 2017 Springer Nature Singapore Pte Ltd.

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Zhang, D., Guo, D., Yan, K. (2017). A Novel Medical E-Nose Signal Analysis System. In: Breath Analysis for Medical Applications. Springer, Singapore. https://doi.org/10.1007/978-981-10-4322-2_15

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  • DOI: https://doi.org/10.1007/978-981-10-4322-2_15

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-4321-5

  • Online ISBN: 978-981-10-4322-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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