A CPU of a health management apparatus functions as an acquisition unit, a first derivation unit, and a screen output control unit. The acquisition unit acquires a body-fat percentage which is an obesity parameter indicating the degree of obesity of a target pet and bone density which is a bone parameter indicating the degree of bone strength of the target pet. The first derivation unit derives health conditions of the target pet on the basis of a correlation between the body-fat percentage and the bone density. A screen output control unit performs control to output a medical examination result display screen on which the health conditions are displayed.

A method for non-invasive quantification of organ fat using a magnetic resonance approach includes: constructing a detection system; connecting a detection area; detection system startup; acquiring data; analyzing data; and performing horizontal data analysis. An external computer, a radio frequency (RF) subsystem, and a portable magnet module are used to construct a system for non-invasive quantification of organ fat based on low-field nuclear magnetic resonance (LF-NMR), which causes no damage, and achieves accurate and non-invasive quantification of organ fat. Specific pulse sequences are used to excite nuclear spin in a target region to generate LF-NMR, so as to achieve “one-click” detection, which is used for fast screening of related diseases such as non-alcoholic fatty liver disease (NAFLD). The system has accurate quantification, and is easy to operate without constraints of operator qualifications.

A method for a wearable device to determine a biological parameter of a tissue of a person. To apply an emitting of a first and a second wavelength of light towards the tissue. To collect and sense a first and a second set of frequency bands from the signals received back from the first and the second wavelengths respectively. The first set of frequency bands represents a first signal which corresponds to a combination of the biological parameter and an extraneous noise. The second set of frequency bands represents a second signal mainly comprising the extraneous noise. To subtract the first set of frequency bands from the second set of frequency bands in the frequency domain to obtain a third set of frequency bands. The third set of frequency bands represents a third signal corresponding to the biological parameter.

A health management apparatus includes a processor that is configured to activate a sugoroku including squares linking a starting square with a finishing square and direct a piece of a user to be advanced through the squares. The processor is configured to obtain measurement data including biological information of the user and a time of day or location of measurement at which the biological information has been measured. The processor is configured to assess an evaluation value based on whether the time of day or location of measurement satisfies a condition, and determine a number of squares through which the piece is to be advanced in the sugoroku, based on the evaluation value.

An apparatus for estimating lipid concentration is provided. According to an example embodiment, the apparatus may include a training data collector configured to collect, as training data, a reference lipid concentration measured through blood samples of a plurality of users for a predetermined time period and sensor data obtained through light signals detected from the plurality of users for the predetermined time period and a processor configured to perform preprocessing including a moving average and data augmentation on the obtained sensor data, select a valid variable relevant to a change in lipid concentration based on the preprocessed sensor data and the reference lipid concentration, and generate a lipid concentration prediction model based on the selected valid variable.

An apparatus for non-invasive evaluations and in-vivo diagnostics includes an open magnet, an RF antenna, and an NMR analytics logical circuit communicatively coupled to the RF antenna, wherein the open magnet is shaped to generate a static magnetic field that extends unilaterally into an object or internal organ of a subject when the open magnet is positioned against or in proximity to the object or subject, the static and RF magnetic fields shaped to generate a sensitive volume within a target region. The RF antenna or antenna array is configured to transmit RF pulses into the target region of the object or internal organ and receive sets of NMR signals generated by hydrogen or other elements, and the NMR analytics logical circuit is configured to obtain and analyze sets of NMR signals.

Methods, systems and computer readable media for computerized prediction of body parameters such as body fat percentage (BFP) and modeling of a subject (e.g., a human body) are described.

A Raman sensor includes a light source assembly having a plurality of light sources configured to emit light to a plurality of skin points of skin, each of the plurality of skin points having a predetermined separation distance from a light collection region of the skin from which Raman scattered light is collected; a light collector configured to collect the Raman scattered light from the light collection region of the skin; and a detector configured to detect the collected Raman scattered light.

For tissue property estimation with ultrasound, multiple different types of measurements are performed by an ultrasound system, including scatter measurements and shear wave propagation measurements. The tissue property, such as liver fat fraction, is estimated using a combination of these different types of measurements.

A method for non-invasive quantification of organ fat using a magnetic resonance approach includes: constructing a detection system; connecting a detection area; detection system startup; acquiring data; analyzing data; and performing horizontal data analysis. An external computer, a radio frequency (RF) subsystem, and a portable magnet module are used to construct a system for non-invasive quantification of organ fat based on low-field nuclear magnetic resonance (LF-NMR,), which causes no damage, and achieves accurate and non-invasive quantification of organ fat. Specific pulse sequences are used to excite nuclear spin in a target region to generate LF-NMR, so as to achieve “one-click” detection, which is used for fast screening of related diseases such as non-alcoholic fatty liver disease (NAFLD). The system has accurate quantification, and is easy to operate without constraints of operator qualifications.