Described herein are devices and methods for continuous real time monitoring of kidney function. In various embodiments, a urine analysis device collects sensor data describing one or more properties of urine. The urine analysis device may be integrated with a catheter system to continuously generate sensor data in real time as the urine is collected by the catheter system. Sensor data collected by the urine analysis device may be analyzed by physicians to detect changes in a patients kidney function. If necessary, based on the sensor data, physicians may perform an intervention to improve a patients kidney function.

Improved assessment of brain injuries, and improved brain injury management, is achieved using a combination of impact-related data derived from instrumented mouthguard devices, human function performance testing, and biomarkers derived from biological fluid (such as saliva and/or blood). The human function performance testing may include brain function performance testing, and/or other forms of human function performance testing. This involves combining a data-driven understanding of a head impact event (based on data collected via an instrumented mouthguard device) with a data-driven understanding of human function performance following that head impact event. The biomarkers may include salivary mRNA and/or ncRNA, and/or blood proteins (for example via a FDA-approved Brain Trauma Indicator test).

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.

A method for monitoring a patient in a bed using a camera. The method includes identifying a boundary of the bed using data from the camera, identifying parts of the patient using data from the camera, and determining an orientation of the patient using the parts identified for the patient. The method further includes monitoring movement of the patient using the parts identified for the patient and computing a departure score indicating the likelihood of the patient departing the bed based on the orientation of the patient and the movement of the patient. The method further includes comparing the departure score to a predetermined threshold and generating a notification when the departure score exceeds the predetermined threshold.

Systems and methods for enhancing infection detection and monitoring through decomposed physiological data are disclosed. An example method includes receiving, from a wearable device of a user, physiological data of the user and decomposing the physiological data, by applying a heart rate algorithm, to generate one or more physiological parameters. The example method further includes analyzing, by applying the heart rate algorithm, the one or more physiological parameters to output a period classification, and determining whether or not the period classification is indicative of an infection. The example method further includes, responsive to determining that the period classification is indicative of the infection, displaying, in a user interface, a warning to the user that indicates the infection, and receiving, from the wearable device of the user, additional physiological data of the user to monitor the infection.

A method and system are provided for estimating a physiological parameter using a parameter model determined by a deep neural network. An example method includes training a deep neural network with indirect and direct physiological parameters from a user database. The medical parameters include a respiratory rate, oxygen saturation, temperature, blood pressure, and pulse rate. The method includes determining if a new user belongs in a group. If the parameter model estimated physiological parameter using the closest group to the new user and associated calibration, then the method quantizes the parameter inputs to determine which physiological parameter a new user is most sensitive and to determine a new group and calibration coefficients or curves for the new user.

An apparatus including circuitry configured to determine a probability by combining at least: a probability that an event is present within a current feature of interest given a first set of previous features of interest, and a probability that the event is present within the current feature of interest given a second set of previous features of interest, different to the first set of previous features of interest; circuitry configured to detect the event based on the determined probability; and circuitry configured to control, in dependence on the detection of the event, performance of an action.

An adjustable measurement device is described that may include a housing, a power supply, a processor, a communication device, an elastic coupling member, a physiological sensor, and/or a clamp. The housing may be configured to attach to a wearable band that is wearable by a subject. The housing may include a chamber within the housing. The power supply, the processor, the communication device, the elastic coupling member, and or the physiological sensor may be disposed within the chamber. The elastic coupling member may couple the physiological sensor to the housing. A force exerted by the elastic coupling member on the physiological sensor may be in a direction through an opening towards a body part of a subject. As the subject wears the wearable band and the housing is coupled to the wearable band, the physiological sensor may be adjacent to or contact the subject.

A method of quantitatively evaluating a cognitive impairment and its future change from a medical image of an individual's brain, the method comprising scanning the individual's brain with a scanning device so as to acquire at least one medical brain image; processing the medical brain image to obtain at least one feature of the image; using a pre-established prediction model to determine a condition of the cognitive impairment and predict its future change based on the at least one feature obtained.

An emergency cardiac and electrocardiogram (ECG) electrode placement device with artificial intelligence is disclosed herein. The emergency cardiac and electrocardiogram (ECG) electrode placement device incorporates electrical conducting materials and elastic material into a pad that is applied to a chest wall of a patient, which places multiple electrodes in the appropriate anatomic locations on the patient to quickly obtain an ECG in a pre-hospital setting. The AI program continuously runs EKGs to continuously monitor a patient.