Binary Fingerprints at Fluctuation-Enhanced Sensing

We 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 25 thousands to 1 million. 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.Comment: submitted for publicatio

Ternary Fingerprints with Reference Odor for Fluctuation-Enhanced Sensing

An improved method for Fluctuation Enhanced Sensing (FES) is introduced. We enhanced the old binary fingerprinting method, where the fingerprint bit values were +/- 1, by introducing ternary fingerprints utilizing a reference odor. In the ternary method, the fingerprint bit values are -1, 0, and +1 where the 0 value stands for the situation where the slope of the spectrum is identical to that of the reference odor. The application of the reference odor spectrum makes the fingerprint relative to the reference. This feature increases the information entropy of the fingerprints. The method is briefly illustrated by sensing bacterial odor in cow manure isolates.Comment: submitted for publicatio

Power spectral density estimation for wireless fluctuation enhanced gas sensor nodes

Fluctuation enhanced sensing (FES) is a promising method to improve the selectivity and sensitivity of semiconductor and nanotechnology gas sensors. Most measurement setups include high cost signal conditioning and data acquisition units as well as intensive data processing. However, there are attempts to reduce the cost and energy consumption of the hardware and to find efficient processing methods for low cost wireless solutions. In our paper we propose highly efficient signal processing methods to analyze the power spectral density of fluctuations. These support the development of ultra-low-power intelligent fluctuation enhanced wireless sensor nodes while several further applications are also possible

Fluctuation enhanced gas detector for wireless sensor networks

Spontaneously produced Unfilled Pauses (UPs) andFilled Pauses (FPs) were played to subjects in an fMRI experiment. While both stimuli resulted in increased activity in the Primary Auditory Cortex, FPs, unlike UPs, also elicited modulation in the Supplementary Motor Area, Brodmann Area 6. This observation provides neurocognitive confirmation of the oft-reported difference between FPs and other kinds of speech disfluency and also could provide a partial explanation for the previously reported beneficial effect of FPs on reaction times in speech perception. The results are discussed in the light of the suggested role of FPs as floor-holding devices in human polylogs

Bacteria Identification by Phage Induced Impedance Fluctuation Analysis (BIPIF)

We present a new method for detecting and identifying bacteria by measuring impedance fluctuations (impedance noise) caused by ion release by the bacteria during phage infestation. This new method significantly increases the measured signal strength and reduces the negative effects of drift, material aging, surface imperfections, 1/f potential fluctuations, thermal noise, and amplifier noise. Comparing BIPIF with another well-known method, bacteria detection by SEnsing of Phage Triggered Ion Cascades (SEPTIC), we find that the BIPIF algorithm is easier to implement, more stable and significantly more sensitive (by several orders of magnitude). We project that by using the BIPIF method detection of a single bacterium will be possible.Comment: Submitted for publication. US Navy - Texas A&M University, joint patent pendin

Sensing Applications of Fluctuations and Noise

Noise and time-dependent fluctuations are usually undesirable signals. However, they have many applications. This dissertation deals with two kinds of sensing applications of fluctuation and noise: soil bulk density assessment and bacterium sensing. The measurement of Vibration-Induced Conductivity Fluctuations (VICOF) provides information about the bulk density and other parameters of soils. Bulk density is the physical property of soils that is important to both the agriculture and construction industries. The traditional measurements of soil bulk density are often time-consuming, expensive or destructive. To determine the soil bulk density without the above drawbacks, the VICOF measurement scheme was proposed. The research of VICOF in this dissertation includes two parts: the initial phase of study and the new methods and their theory. In the initial phase of study, the simple experiments, theory, and simulations of VICOF were tested for relations between the soil bulk density, wetness, salinity, and the VICOF data. Then, new measurement arrangements and their theoretical models were proposed to improve the weaknesses of the initial approach (such as large scattering of data due to loose and heavy contacts) and to calculate the relationship between the measured signals and the electromechanical transport parameters of the soils. The bacterium sensing study in this dissertation was proposed to explore simple, practical, rapid, sensitive, specific, portable, and inexpensive ways to detect and recognize bacteria by Fluctuation-Enhanced Sensing (FES). One such potential way of bacterium sensing is to analyze their odor. The research of bacterium sensing also includes two parts: the initial phase of study and the new methods and their theory. The initial phase study was proposed to explore the possibility of detecting and identifying bacteria by sensing their odor via FES with commercial Taguchi sensors. Then the subsequently developed new methods and their theory provide a simple way to generate binary patterns with perfect reproducibility based on the spectral slopes in different frequency ranges at FES. This new type of signal processing and pattern recognition is implemented at the block diagram level using the building elements of analog circuitries and a few logic gates with total power consumption in the microWatts range