Various embodiments are described herein for a system and associated method for performing collagen assessment of an object using Photoacoustic Image (PA) data obtained for the object, wherein the method is performed by a processing unit and the method comprises: obtaining beamformed PA image data for the object using at least three wavelengths related to chromophores including collagen, oxyhemoglobin and deoxyhemoglobin, the three wavelengths being less than 1000 nm; performing spectral decomposition on the beamformed PA image data using the three wavelengths to obtain data that is used for generating at least one collagen map; and determining a collagen score for the at least one collagen map.

A method is for providing respiratory information. In an embodiment, the method includes receiving imaging data relating to a lung; calculating a perfusion fraction for each respective region of a set of regions of the lung, based on the imaging data; calculating a respective ventilation value for each respective region of the set of regions of the lung based on the imaging data; calculating a weighted average of respective ventilation values across all respective regions of the set of regions of the lung, wherein for each respective region of the set of regions of the lung, the respective ventilation value of the respective region is weighted with the perfusion fraction of the respective region; generating the respiratory information based on the weighted average of the respective ventilation values; and providing the respiratory information.

A method for uterine activity monitoring may include: acquiring a plurality of signals from a plurality of sensors during uterine activity; processing the plurality of signals to extract a plurality of uterine electrical activity characteristics; analyzing the plurality of uterine electrical activity characteristics; and classifying the uterine activity as one of: a preterm labor contraction, a labor contraction, a Braxton-Hicks contraction, and a state of no contraction. A method of assessing over time a pre-term birth risk of a pregnant female may include: calculating a baseline pre-term birth risk score based on a user input; acquiring, over time, a signal from a sensor; analyzing the signal to extract a parameter of interest, such that the parameter of interest comprises a physiological parameter; and calculating an instant pre-term birth risk score based, at least in part, on the parameter of interest and the user input.

Systems, methods, and computer-readable media for providing a decision support solution to medical professionals to optimize medical care through data monitoring and feedback treatment are provided herein. In another embodiment, a computer-implemented method for modeling patient outcomes resulting from treatment in a specific medical area includes receiving patient-specific data associated with a patient, determining a plurality of possible patient states under which the patient can be categorized, a current patient state under which the patient can be categorized and determining probabilities of the patient transitioning from any of the possible patient states to every other possible patient state.

An apparatus device may include a bio-impedance sensor configured to take a bio-impedance measurement from a body of an individual, an optical sensor configured to take an optical measurement from the body of the individual, and a processing device configured to receive a first bio-impedance measurement from the bio-impedance sensor taken during a first period of time and a first optical measurement from the optical sensor taken during the first period of time, receive first location information of the individual during the first period of time, determine a first correlation between a physiological parameter and at least one of the first location, the first bio-impedance measurement, or the first optical measurement, and determine a first level of the physiological parameter based on the first correlation.

Computer implemented biometric methods and systems incorporate sensing biophysical phenomena, translating the phenomena into digital data and transmitting the data to a series of servers operating in an open feedback loop to generate a module. A biometric networking system can include a biometric monitoring cloud computing platform with AI/machine learning augmented models are generated to make user assessments, programs and confidence scores to the healthcare provider systems. The AI/machine learning models can be used by the biometric monitoring network to generate health-related AI processes that analyze relationships treatment techniques and outcomes. AI techniques can be used to calculate movement modeling and confidence scoring including support vector machines, neural networks, and decision trees. The biophysical phenomena may include biometric parameters based on data, such as medical history, exertion, sleep, temperature, cardiovascular events, respiratory events, and muscle and blood pH.

A method of passively detecting radiofrequency (RF) signals spontaneously emitted by a non-equilibrium population of electrons that are spin polarized by flowing through a chiral media during relaxation of the spin polarized electrons to equilibrium at a frequency corresponding to a Zeeman spin-flip energy of the spin polarized electrons under influence of a magnetic field (MF). The MF is applied to the chiral media for a predefined time period to shift a frequency and magnitude of the spontaneously emitted RF signals in line with Zeeman effect. The shifted emitted RF signals is passively detected and stored for medical use applications using a receiver antenna tuned to a resonant frequency of the shifted emitted RF signals.

The application is directed to devices and methods where one or more magnetic or magnetizable implants provides therapeutic benefits to a patient. The implant may be useful for expanding the range of motion of joints or dynamically providing different responses to changing conditions in the body where the implant is placed. An electromagnet is placed on or in a bone on one side of a joint, and another electromagnet or magnetically active material is placed on or in a bone on the opposing side of the joint. The electromagnet may be continuously energized to relieve pressure in the joint space, or may be energized in response to forces applied to the joint.

The present invention relates to a decision support system (DSS), a medical monitoring system (100), and a corresponding method for identifying the need for measurement of cardiac output (CO) based on one or more comparisons (COMP1, COMP2) in a physiological model. More specifically, for identifying when an approximated value of CO cannot be correct due to circulatory compromise and as such that another estimated or measured value of CO is required.

Sensing devices including sensors such as flexible and stretchable fabric-based pressure sensors, may be associated with or incorporated in garments, such as socks, intended to be worn against a body surface (directly or indirectly). Specific manifestations of a sensing system incorporated in a sock substrate are described in detail. Dedicated electronic devices interface electrically with sensors through intermediate conductive traces, optional conductive bridges, conductive contacts provided in a mounting tab.