Breath alcohol, multisensor arrays, and electronic noses

Nils Paulsson; Fredrik Winquist

doi:10.1117/12.265395

28 January 1997 Breath alcohol, multisensor arrays, and electronic noses

Nils Paulsson, Fredrik Winquist

Proceedings Volume 2932, Human Detection and Positive Identification: Methods and Technologies; (1997) https://doi.org/10.1117/12.265395
Event: Enabling Technologies for Law Enforcement and Security, 1996, Boston, MA, United States

Abstract

The concept behind a volatile compound mapper, or electronic nose, is to use the combination of multiple gas sensors and pattern recognition techniques to detect and quantify substances in gas mixtures. There are several different kinds of sensors which have been developed during recent years of which the base techniques are conducting polymers, piezo electrical crystals and solid state devices. In this work we have used a combination of gas sensitive field effect devices and semiconducting metal oxides. The most useful pattern recognition routine was found to be ANNs, which is a mathematical approximation of the human neural network. The aim of this work is to evaluate the possibility of using electronic noses in field instruments to detect drugs, arson residues, explosives etc. As a test application we have chosen breath alcohol measurements. There are several reasons for this. Breath samples are a quite complex mixture contains between 200 and 300 substances at trace levels. The alcohol level is low but still possible to handle. There are needs for replacing large and heavy mobile instruments with smaller devices. Current instrumentation is rather sensitive to interfering substances. The work so far has dealt with sampling, how to introduce ethanol and other substances in the breath, correlation measurements between the electronic nose and headspace GC, and how to evaluate the sensor signals.

Citation Download Citation

Nils Paulsson and Fredrik Winquist "Breath alcohol, multisensor arrays, and electronic noses", Proc. SPIE 2932, Human Detection and Positive Identification: Methods and Technologies, (28 January 1997); https://doi.org/10.1117/12.265395

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