Aspects relate to an optical fluid analyzer including a fluid cell configured to receive a sample fluid. The optical fluid analyzer further includes optical elements configured to seal the fluid cell on opposing sides thereof and to allow input light from a light source to be sent through the fluid cell and output light from the fluid cell to be input to a spectrometer. The optical fluid analyzer further includes a machine learning (ML) engine, such as an artificial intelligence (AI) engine, that is configured to generate a result defining at least one parameter of the fluid based on a spectrum produced by the spectrometer.

An analysis method for analyzing a sample includes a first step of acquiring measurement data including a first signal based on the sample and a second signal based on noise added to the first signal as a result of analysis of the sample, a second step of assuming a shape representing the first signal and a shape representing the second signal and modeling the measurement data using Bayesian inference, and a third step of estimating a probability distribution of characteristics of the sample based on the modeled measurement data.

According to a first aspect of the present invention there is provided a method of measuring the optical reflectance R of a target using a detection system comprising a light emitter and a light detector spaced apart from one another. The method comprises illuminating the target with the light emitter, detecting light reflected from the target using the light detector, wherein the light detector provides an electrical output signal S.sub.S indicative of the intensity of the detected light, and determining the optical reflectance R of the target according to (Formula 1), where R.sub.R is the spectral reflectance of a reference standard, S.sub.R is the detector electrical output signal with the reference standard in place, S.sub.H is the detector electrical output signal with no target in front of the light emitter and light detector, and M is a calibration factor.

[00001]$\begin{array}{cc}R=M.Math.R_R\frac{s_s-s_H}{M.Math..Math.s_R-s_H.Math.-R_R.Math.s_R-s_s.Math.},& \left(1\right)\end{array}$

Automated camera-based optical assessment involves color assessment of a physical object using conventional and inexpensive computer hardware such as a smartphone. A specially-configured test card includes a body supporting a reagent pad configured to change to an expected color in response to an enzymatic reaction, and an imaging key adjacent the reagent pad. The imaging key includes color fields including at least one field of the expected color. The hardware captures an image of the test card, and processes the image to identify the reagent pad and color fields, to process a brightness calibration target, to determine color values for the reagent pad and color fields, to calibrate the color values as a function of brightness and/or color by comparison to the brightness and color calibration targets, and to identify a color field most closely matching the reagent pad's color to determine a corresponding test result.

Optical property measurement using a sensor behind a display screen Examples of this application disclose a method for measuring optical properties of a target. The method comprises illuminating the target with an illumination area with a display screen in contact with the target, and analysing signals reflected from the target and transmitted back through the display screen to a sensor positioned behind the display screen, to determine the optical properties of the target.

Methods, devices, apparatus, and systems for three-dimensional (3D) contoured scanning photoacoustic imaging and/or deep learning virtual staining.

A test sensor for determining an analyte concertation in a biological fluid comprises a strip including a fluid receiving area and port-insertion region. A first row of optically transparent and non-transparent positions forms a calibration code pattern disposed within a first area of the port-insertion region. A second row of optically transparent and non-transparent positions forms a synchronization code pattern disposed within a second area of the port-insertion region. The second area is different from the first area. The synchronization code pattern corresponds to the calibration code pattern such that the synchronization code pattern provides synchronization of the serial calibration code pattern during insertion of the port-insertion region into the receiving port of the analyte meter.

Provided are an automatic analyzer and an optical measurement method for correcting a variation in the multiplication factor of a photoelectric element with high accuracy. The automatic analyzer comprises: a photoelectric element which generates electrons by light and outputs a current signal; a voltage application unit which applies a voltage to the photoelectric element; and a processing unit which corrects a variation in the multiplication factor of the photoelectric element, wherein the photoelectric element outputs a pulse signal as the current signal, and the processing unit corrects the variation in the multiplication factor on the basis of the pulse area of the pulse signal.

An optical sensing system includes at least one electro-optical sensor having an adjustable field of view and at least one reflective member including a diffuse reflector surface positioned within the field of view of the at least one electro-optical sensor. The system also includes at least one controller configured to generate calibration parameters for the at least one electro-optical sensor based on data for at least one exposure detected by the electro-optical sensor when the diffuse reflector surface is within the field of view of the at least one electro-optical sensor. Methods for calculating the calibration parameters and for directly measuring reflectivity of objects in a scene with at least one electro-optical sensor are also disclosed herein.

In order to make it possible to conduct a zero calibration even though an interference gas exists in a measurement area of a detector, a light absorbance analysis apparatus includes a detector that detects an intensity of light that transmits a gas, a total pressure sensor that measures a total pressure of the gas, an absorbance calculating part that calculates an absorbance based on an output value of the detector and a previously set zero reference value, a partial pressure—absorbance relation storing part that stores a partial pressure—absorbance relational data that indicates a relationship between a partial pressure of an interference gas that exists in a measurement area of the detector and an absorbance calculated by the absorbance calculating part, and a partial pressure calculating part that calculates an interference gas partial pressure as a partial pressure of the interference gas.