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Improving the performance of electronic nose for wound infection detection using orthogonal signal correction and particle swarm optimization

Jingwei Feng (College of Communication Engineering, Chongqing University, Chongqing, China)
Fengchun Tian (College of Communication Engineering, Chongqing University, Chongqing, China)
Pengfei Jia (College of Communication Engineering, Chongqing University, Chongqing, China)
Qinghua He (Department of Orthopedic and Traumatic Surgery, Center for War Wound and Trauma of PLA, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, China)
Yue Shen (Department of Orthopedic and Traumatic Surgery, Center for War Wound and Trauma of PLA, Institute of Surgery Research, Daping Hospital, Third Military Medical University, Chongqing, China)
Shu Fan (College of Communication Engineering, Chongqing University, Chongqing, China)

Sensor Review

ISSN: 0260-2288

Article publication date: 26 August 2014

Abstract

Purpose

The purpose of this paper is to detect wound infection by electronic nose (Enose) and to improve the performance of Enose.

Design/methodology/approach

Mice are used as experimental subjects. Orthogonal signal correction (OSC) is applied to preprocess the response of Enose. Radical basis function (RBF) network is used for discrimination, and the parameters in RBF are optimized by particle swarm optimization.

Findings

OSC is very suitable for eliminating interference and improving the performance of Enose in wound infection detection.

Research limitations/implications

Further research is required to sample wound infection dataset of human beings and to demonstrate that the Enose with proper algorithms can be used to detect wound infection.

Practical implications

In this paper, Enose is used to detect wound infection, and OSC is used to improve the performance of the Enose. This widens the application area of Enose and OSC.

Originality/value

The innovative concept paves the way for the application of Enose.

Keywords

Acknowledgements

This work was financially supported by the Fundamental Research Funds for the Central Universities (Project No. CDJXS12162212).

Citation

Feng, J., Tian, F., Jia, P., He, Q., Shen, Y. and Fan, S. (2014), "Improving the performance of electronic nose for wound infection detection using orthogonal signal correction and particle swarm optimization", Sensor Review, Vol. 34 No. 4, pp. 389-395. https://doi.org/10.1108/SR-10-2012-710

Publisher

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Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited