Abstract:
A system and method for assessing the presence or absence of a pathogenic microorganism in a biological sample. the sample is irradiated to generate interacted photons which are used to generate at least one Raman data set represetnive of the sample. The Raman data set may comprise at least one of: a Raman spectrum and a Raman chemical image. The Raman chemical image may comprise a hyperspectral image. The method may further identify the pathogenic microorganism and associate it with a particular microbiome, such as the digestive system. The method may further associate the sample with a disease state and/or stage.
Abstract:
A system and method for multipoint assessment of a biological sample, which may comprise a bodily fluid. The sample is irradiated to generate a plurality of interacted photons. These photons are assessed to evaluate a component of the sample. The component may comprise at least one of: a protein, a flavonoid, a keratinoid, a metabolite, an electrolyte, an enzyme, and combinations thereof. The component may also comprise at least one of: a chemical agent, a biological toxin, a microorganism, a bacterium, a protozoan, a virus, and combinations thereof. The evaluation may comprise determining at least one of: a disease state, a disease stage, a metabolic state, a hydration state, an inflammatory state, and combinations thereof.
Abstract:
A first location comprising an unknown material may be scanned using SWIR hyperspectral imaging in a dual polarization configuration. Surveying may also be applied to thereby determine whether or not a human is present. This surveying may be achieved my assessing LWIR data, data acquired from motion sensors, and combinations thereof. If no human is present, a second location may be interrogated using Raman spectroscopic techniques to thereby obtain a Raman data set representative of the region of interest. This Raman data set may be assessed to associate an unknown material with a known material. This assessment may be achieved by comparing the Raman data set to one or more reference data sets in a reference database, where each reference data set is associated with a known material.
Abstract:
A system and method for analyzing unknown materials on surfaces including, but not limited to, chemical materials, biological materials, hazardous materials, drug materials, and non-threat materials using SWIR and/or extended range SWIR hyperspectral and spectroscopic techniques. A system comprising a collection optics, a tunable filter, and a first detector for generating a test data set representative of the unknown sample. A second detector, comprising a visible imaging device, may be configured to operate in a scanning mode to locate areas of interest for further interrogation using SWIR. A method comprising generating a SWIR test data set representative of the unknown sample and analyzing the unknown sample to detect, identify and/or distinguish an unknown material as a known material. This analysis may be achieved by comparing the test data set to a reference data set using at least one chemometric technique.