Binary Fingerprints at Fluctuation-Enhanced Sensing
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Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA
2
Department of Mechanical Engineering, Texas A&M University, College Station, TX 77843-3123, USA
3
Signal Processing, Inc., 13619 Valley Oak Circle, Rockville, MD 20850, USA
*
Author to whom correspondence should be addressed.
Sensors 2010, 10(1), 361-373; https://doi.org/10.3390/s100100361
Received: 8 December 2009
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Revised: 23 December 2009
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Accepted: 28 December 2009
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Published: 5 January 2010
(This article belongs to the Special Issue Metal-Oxide Based Nanosensors)
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.
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Keywords:
fluctuation-enhanced sensing; semiconducting metal oxide sensors; nano-sensors; ultra-low power sensor systems
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MDPI and ACS Style
Chang, H.-C.; Kish, L.B.; King, M.D.; Kwan, C. Binary Fingerprints at Fluctuation-Enhanced Sensing. Sensors 2010, 10, 361-373. https://doi.org/10.3390/s100100361
AMA Style
Chang H-C, Kish LB, King MD, Kwan C. Binary Fingerprints at Fluctuation-Enhanced Sensing. Sensors. 2010; 10(1):361-373. https://doi.org/10.3390/s100100361
Chicago/Turabian StyleChang, Hung-Chih, Laszlo B. Kish, Maria D. King, and Chiman Kwan. 2010. "Binary Fingerprints at Fluctuation-Enhanced Sensing" Sensors 10, no. 1: 361-373. https://doi.org/10.3390/s100100361
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