Machine learning systems and methods are disclosed for prediction of wound healing, such as for diabetic foot ulcers or other wounds, and for assessment implementations such as segmentation of images into wound regions and non-wound regions. Systems for assessing or predicting wound healing can include a light detection element configured to collect light of at least a first wavelength reflected from a tissue region including a wound or portion thereof, and one or more processors configured to generate an image based on a signal from the light detection element having pixels depicting the tissue region, automatically segment the pixels into wound pixels and non-wound pixels, determine one or more optically determined tissue features of the wound or portion thereof, and generate a predicted or assessed healing parameter associated with the wound or portion thereof over a predetermined time interval.

A diabetic complications monitoring apparatus and a diabetic complications monitoring system using the same, includes a support fixture having a liquid crystal color changing sheet that is located on an upper surface of the support fixture and displays a foot heat distribution based on a color, a transparent glass that is located on an upper surface of the liquid crystal color changing sheet and comes into contact with user's feet to support the user's feet, a foot heat distribution measurement unit that includes a camera for imaging the liquid crystal color changing sheet and extracts and outputs a foot heat distribution from an image of the camera, a processor that acquires and outputs whether a disease occurs, or a position and size of occurrence of a disease, based on the foot heat distribution, and a data input/output device that audioizes and visualizes an output result of the processor.

Systems and methods to determine an indication of patient compliance are disclosed, including detect temperature information associated with a treatment device comprising a therapy component including at least one of an electrical therapy component or a thermal therapy component configured to apply a treatment at the treatment location and determining the indication of patient compliance using the received temperature information occurring over a first period.

A ring-type wearable device is provided for sensing biometric data associated with various physiological conditions of the user. In one embodiment, a ring apparatus comprises a ring body including an opening formed therethrough structured to receive a body portion of a user therein when worn by the user; and an electronic computer processor programmed for processing one or more signals detected by the apparatus and associated with one or more biometrics associated with a physiological condition of the user into processed data. A light sensor system connected to the ring body includes multiple light-emitting diodes (LEDs), wherein each LED is associated with a predetermined light wavelength range, a first photodetector configured for light detection in a reflection mode, and a second photodetector configured for light detection in a transmission mode, each for detecting at least a portion of the light originating from the multiple LEDs.

The present disclosure provides a device with electrodes configured to record electrical activity that are confined to a restricted area, using recorded biological electrical signals to control cursor position in a speech-assistance interface, and using recorded biological signals to detect arousals during sleep.

Provided herein is a method and system for the estimation of apnea-hypopnea index (AHI), as an indicator for Obstructive sleep apnea (OSA) severity, by combining speech descriptors from three separate and distinct speech signal domains. These domains include the acoustic short-term features (STF) of continuous speech, the long-term features (LTF) of continuous speech, and features of sustained vowels (SVF). Combining these speech descriptors may provide the ability to estimate the severity of OSA using statistical learning and speech analysis approaches.

The present disclosure provides an oral data collection device comprising a mouthguard and at least two sensors, a medical analytics system comprising the device, and methods of using the device and system to provide a personalized treatment protocol, stage a health condition, measure a response to therapy, phenotype for selection to participate in drug trials, measure stability of an anatomical structure, or predict a rate of change of a health condition in a subject in need thereof.

Various methods and systems are provided for automatically generating a recommendation to downgrade a patient from an intensive care unit (ICU) to a different medical unit. In one embodiment, a method for a patient downgrade recommendation system comprises, for each patient of a plurality of selected patients of the ICU, selecting a set of downgrade criteria for the patient; from a first, larger set of patient data of the patient, automatically compiling a second, smaller set of patient data based on the set of downgrade criteria; applying a set of rules associated with the set of downgrade criteria to the second, smaller set of patient data to generate a downgrade recommendation for the patient; and arranging the graphical downgrade recommendation elements of the plurality of selected patients in a single integrated view of a user interface a display device of the patient downgrade recommendation system.

An apparatus for early detection of sepsis in a host is disclosed. The apparatus includes a first sensor to directly measure a glucose level, a second sensor to directly measure a lactate level and a third sensor to directly measure a tissue oxygen level. The first sensor, the second sensor, and the third sensor all being inserted at a single point of entry in a subcutaneous space of the host such that a predetermined correlation between the glucose level, lactate level, and tissue oxygen level signals conditions related to sepsis.

A method of assessing a subject including: measuring a plurality of respirations of the subject; determining one or more respiration parameter from the plurality of respirations; and determining, using the one or more respiration parameter, one or more of: a state of consciousness of the subject; and a prognosis of the subject.