Abstract: Methods for detection and identification of bacteria within a sample include the step of inserting a pair of electrodes into the sample. A first impedance across the electrodes is established with a first AC voltage source having a first frequency. A phage is introduced into the sample, and impedance fluctuations that are caused by ion release by the bacteria due to the phage introduction are measured. The use of impedance fluctuations instead of voltage fluctuations to detect and identify bacteria minimizes 1/f noise effects and increases system sensitivity. To further increase system sensitivity by eliminating thermal noise, a second impedance across the electrodes can be established using a second AC voltage source at a second frequency. Second impedance fluctuations are cross-correlated to the first impedance fluctuations, and the cross-correlation results are analyzed to determine whether or not bacteria are present in the sample based on phage electrical activity.

Abstract: Methods for detection and identification of bacteria within a sample include the step of inserting a pair of electrodes into the sample. A first impedance across the electrodes is established with a first AC voltage source having a first frequency. A phage is introduced into the sample, and impedance fluctuations that are caused by ion release by the bacteria due to the phage introduction are measured. The use of impedance fluctuations instead of voltage fluctuations to detect and identify bacteria minimizes 1/f noise effects and increases system sensitivity. To further increase system sensitivity by eliminating thermal noise, a second impedance across the electrodes can be established using a second AC voltage source at a second frequency. Second impedance fluctuations are cross-correlated to the first impedance fluctuations, and the cross-correlation results are analyzed to determine whether or not bacteria are present in the sample based on phage electrical activity.

Abstract: Methods for detection and identification of bacteria within a sample include the step of inserting a pair of electrodes into the sample. A first impedance across the electrodes is established with a first AC voltage source having a first frequency. A phage is introduced into the sample, and impedance fluctuations that are caused by ion release by the bacteria due to the phage introduction are measured. The use of impedance fluctuations instead of voltage fluctuations to detect and identify bacteria minimizes 1/f noise effects and increases system sensitivity. To further increase system sensitivity by eliminating thermal noise, a second impedance across the electrodes can be established using a second AC voltage source at a second frequency. Second impedance fluctuations are cross-correlated to the first impedance fluctuations, and the cross-correlation results are analyzed to determine whether or not bacteria are present in the sample based on phage electrical activity.

Abstract: A System and Method for Gas Recognition by Analysis of Bispectrum Functions is based on the Higher-Order Spectral analysis of time series measurements of resistance fluctuations in Metal Oxide Semiconductor (MOS) gas sensors, such as Taguchi-type sensors. A two-dimensional contour plot module of the bispectrum function is treated as a pattern. These patterns include information about the analyte(s) whereby characteristics of the gas can be identified.

Abstract: A System and Method of Molecule Counting Using Fluctuation Enhanced Sensors includes processes for improved chemical analyte detection and quantification through the measurement and generation of an amplitude density histogram of the measured time series of frequency fluctuations in the instantaneous frequency of a chemical sensor arranged to produce an oscillatory output signal when exposed to chemical substances. The system and method may use a chemical sensor, such as a surface acoustic wave (SAW) device. Statistical analysis produces the amplitude density of the frequency fluctuations, which are represented as a pattern that includes information about the quantity of the analyte on the surface of the sensor. Patterns in the measured amplitude density are then correlated to theoretical amplitude density functions in order to determine the number of analyte molecules on the surface of the sensor.

Abstract: A system and method of fluctuation enhanced gas-sensing using SAW devices includes processes for improved chemical analyte detection, identification, and quantification through the measurement and spectral analysis of frequency fluctuations in the instantaneous frequency of a chemical sensor arranged to produce an oscillatory output signal when exposed to chemical substances. The system and method may use a chemical sensor, such as a surface acoustic wave (SAW) device. The spectral analysis produces the power spectral density of the frequency fluctuations, which are represented as a pattern that includes information about the analyte(s) such as, total adsorbed gas mass and diffusion coefficients. The diffusion coefficients may then be used to determine the number of molecule types and/or the concentration of each.

Abstract: A signal processor utilizes a globally nonlinearly coupled array of nonlinear dynamic elements. In one embodiment of the invention, these elements take the form of bistable overdamped oscillators. The processor exploits the phenomenon of stochastic resonance to amplify a weak periodic signal embedded in noise. In this signal processor, a system or plurality of nonlinearly coupled overdamped oscillators is subject to a weak periodic signal embedded in a noise background. For communication or detection applications, this weak signal component is the signal of interest. A reference oscillator is chosen from the plurality of overdamped oscillators, and is given a time scale for relaxation that is longer than the remaining oscillators. The output of the reference oscillator is analyzed for signal processing purposes in response to the signal and noise.