Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843-3128, USA.
Sensors (Basel). 2010;10(1):361-73. doi: 10.3390/s100100361. Epub 2010 Jan 5.
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 × 10(4)-10(6). 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.
我们已经开发出一种简单的方法，通过在波动增强感应的不同频率范围内的光谱斜率生成二进制模式。这种模式可以被视为气味的二进制“指纹”。该方法已经通过商业半导体金属氧化物（田口）传感器暴露于细菌气味（大肠杆菌和炭疽替代枯草芽孢杆菌）并处理其随机信号进行了实验证明。使用单个田口传感器，可以以 100%的重现性区分空腔、胰蛋白酶大豆琼脂（TSA）培养基或 TSA 与细菌的情况。细菌数量在 2.5×10(4)-10(6)范围内。为了说明超低功耗的相关性，我们表明这种新型信号处理和模式识别任务可以通过简单的模拟电路和几个逻辑门实现，总功耗在微瓦范围内。
