Odor discrimination using a hybrid-device olfactory biosensor

J. R. Hetling, A. J. Myrick, K. C. Park, T. C. Baker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations


Current trends in artificial nose research are strongly motivated by knowledge of biological olfactory systems, but are primarily confined to improving pattern recognition strategies for data derived from a relatively simple sensor array. Biological olfactory systems are able to discriminate weak, transient, broad-band signals ranging over a poorly-defined parameter space, and therefore outperform current artificial nose systems in several respects. A biological olfactory sense organ, the insect antenna, has been exploited in a hybrid-device biosensor. An algorithm was developed to analyze the electrophysiological responses recorded from a sensor array comprised of antennae from different species of insects. A training period during which the array was exposed to known target odors established response signatures for those odors. Subsequent odor stimuli were then classified using a forced-choice nearest neighbor technique. As odorants arrived in discrete packets in the turbulent air stream, individual sensor response events lasted less than one second, and could be classified with accuracy dependant on the differential tuning of the sensor array to the compounds being classified.

Original languageEnglish (US)
Title of host publicationConference Proceedings - 1st International IEEE EMBS Conference on Neural Engineering
EditorsLaura J. Wolf, Jodi L. Strock
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)0780375793
StatePublished - 2003
Event1st International IEEE EMBS Conference on Neural Engineering - Capri Island, Italy
Duration: Mar 20 2003Mar 22 2003

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554


Other1st International IEEE EMBS Conference on Neural Engineering
CityCapri Island

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Mechanical Engineering


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