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Sensors 2010, 10(1), 361-373;

Binary Fingerprints at Fluctuation-Enhanced Sensing

Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA
Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843-3123, USA
Signal Processing, Inc., 13619 Valley Oak Circle, Rockville, MD 20850, USA
Author to whom correspondence should be addressed.
Received: 8 December 2009 / Revised: 23 December 2009 / Accepted: 28 December 2009 / Published: 5 January 2010
(This article belongs to the Special Issue Metal-Oxide Based Nanosensors)
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We have developed a simple way to generate binary patterns based on spectral slopes in different frequency ranges at fluctuation-enhanced sensing. Such patterns can be considered as binary "fingerprints" of odors. The method has experimentally been demonstrated with a commercial semiconducting metal oxide (Taguchi) sensor exposed to bacterial odors (Escherichia coli and Anthrax-surrogate Bacillus subtilis) and processing their stochastic signals. With a single Taguchi sensor, the situations of empty chamber, tryptic soy agar (TSA) medium, or TSA with bacteria could be distinguished with 100% reproducibility. The bacterium numbers were in the range of 2.5 × 104-106. To illustrate the relevance for ultra-low power consumption, we show that this new type of signal processing and pattern recognition task can be implemented by a simple analog circuitry and a few logic gates with total power consumption in the microWatts range. View Full-Text
Keywords: fluctuation-enhanced sensing; semiconducting metal oxide sensors; nano-sensors; ultra-low power sensor systems fluctuation-enhanced sensing; semiconducting metal oxide sensors; nano-sensors; ultra-low power sensor systems

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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Chang, H.-C.; Kish, L.B.; King, M.D.; Kwan, C. Binary Fingerprints at Fluctuation-Enhanced Sensing. Sensors 2010, 10, 361-373.

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