Backward feature elimination for accurate pathogen recognition using portable electronic nose

Tharmakulasingam M., Topal C., Fernando A., Ragione R. L.

2020 IEEE International Conference on Consumer Electronics, ICCE 2020, Nevada, United States Of America, 4 - 06 January 2020, vol.2020-January identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 2020-January
  • Doi Number: 10.1109/icce46568.2020.9043043
  • City: Nevada
  • Country: United States Of America
  • Keywords: Backward feature elimination, Electronic nose, Machine learning, Pathogen detection
  • Istanbul Technical University Affiliated: Yes

Abstract

This paper presents the application of the backward feature elimination technique on an electronic nose (E-nose) to aid the rapid detection of pathogens using Volatile Organic Compounds (VOCs). The timely identification of pathogens is vital to facilitate control of diseases. E-noses are widely used for the identification of VOCs as a non-invasive tool. However, the identification of VOC signatures associated with microbial pathogens using E-nose is currently inefficient for the timely identification of pathogens. Therefore, we proposed an E-nose system integrating the backward feature elimination. Comprehensive experiments of backward feature elimination showed that they improve the classification accuracy.