A feature extraction method for chemical sensors in electronic noses

L. Carmel*, S. Levy, D. Lancet, D. Harel

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

118 Scopus citations


We propose a new feature extraction method for use with chemical sensors. It is based on fitting a parametric analytic model of the sensor's response over time to the measured signal, and taking the set of best-fitting parameters as the features. The process of finding the features is fast and robust, and the resulting set of features is shown to significantly enhance the performance of subsequent classification algorithms. Moreover, the model that we have developed fits equally well to sensors of different technologies and embeddings, suggesting its applicability to a diverse repertoire of sensors and analytic devices.

Original languageAmerican English
Pages (from-to)67-76
Number of pages10
JournalSensors and Actuators, B: Chemical
Issue number1-3
StatePublished - 1 Aug 2003
Externally publishedYes
EventProceedings of the Ninth International Meeting on Chemical Engineering - Boston, MA, United States
Duration: 7 Jul 200310 Jul 2003


  • Curve fitting
  • Electronic nose
  • Feature extraction
  • Metal-oxide sensors
  • Quartz-microbalance sensors


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