A system (100) and a method for analyzing a physiological condition of a user. The system (100) comprises one or more sensors (102a, 102b) to measure one or more parameters including temperature and relative humidity from the user's skin and/or a corresponding temperature and relative humidity from the user's environment via an air gap. A signal representative of the measured parameters is generated. The system (100) also includes at least one transceiver (108) communicably connectable to the sensing unit (102) via one or more communication interfaces, wherein the transceiver (108) is configurable to analyze one or more received signals to initiate one or more events based on the analyzed parameters of the user. The system (100) further includes a processing unit (110) to receive one or more signals from the transceiver (108) and uses artificial intelligence and machine learning techniques to alert users of an impending physiological condition.

An electronic device for providing a user interface related to a sleep state and an operating method thereof are provided. The electronic device includes a communication circuit, a memory, and at least one processor. The least one processor may be configured to acquire real-time sleep data of a user with regard to a unit sleep session, detect an abnormal rapid eye movement (REM) sleep event based on the real-time sleep data and the user's previous sleep data with regard to a full sleep session, and provide a user interface based on designated action information in response to the abnormal REM sleep event.

Methods and electronic devices for measuring motion and acoustic signatures of physiological processes of a human subject. The method includes measuring motion and acoustic signatures of physiological processes of a human subject; sending the first feature-related data to a machine learning service; sending the first feature-related data to a machine learning service; and determining a predicted detection of human scratching activity by the machine-learning service by performing a machine-learning operation on the feature-related data.

Methods and systems are provided for measuring anatomical dimensions from a single two-dimensional (2D) digital image. The digital image is taken from the front/anterior view using a mobile, handheld communication device. The linear measurements are used to estimate the body volume of the individual. Total body density is calculated from estimated body volume and body weight. Body composition (fat mass and fat-free mass) of the individual is derived from density using known mathematical conversion formulas. A method for estimating body composition analysis is provided.

A psychological evaluation device that estimates interest of a subject in a content used integrally with a terminal held by the subject. Acceleration data obtained by an acceleration sensor built in the terminal is acquired, and a frequency analysis is performed on the acquired acceleration data to obtain acceleration in the gravity direction of the terminal. By obtaining the acceleration in the gravity direction of the terminal, it is possible to, for example, estimate the subject's interest in the content based on the integral value of each frequency component of the acceleration in the gravity direction obtained by performing the frequency analysis.

Disclosed herein is a device for continuous physiological monitoring as well as systems and methods for interpreting data from such a device. The device may support intelligent selection from among two or more different modes for heart rate detection. In addition, the acquisition of continuous physiological data facilitates automated recommendations concerning changes to sleep, recovery time, exercise routines and the like.

A system is provided for automated monitoring the health of a patient. The system is unifying the approach of multi-sensing, robotic platform and cloud computing to monitor the health of the patient with zero or very minimal human intervention. The plurality of physiological parameters and the pathological values is sensed using the plurality of physiological sensors and the plurality of pathological sensors or using a smart phone of the patient. The body of the patient is scanned using a robotic arm. The data sensed by the sensor is then identifies a set of anomalies and send the set of anomalies to cloud server. A cognitive engine present on the cloud server is then diagnoses a disease using cloud computing and send the report to caregiver and doctor. According to another embodiment, a method is also provided for automated monitoring the health of the person using the above mentioned system.

A method and apparatus for stimulating neural activity in the brain of a user of an apparatus with a display screen by causing at least one portion of the display screen to flicker in a controlled manner and utilizing the apparatus to measure an effect on a user exposed to the flicker for a time.

Described are systems for spatial cognitive ability assessment wherein a subject is able to manipulate one or more object(s) that is monitored by a device for recording motion attached to the object(s), the subject, or both that is able to generate motion electronic data. Also described are methods for assessing spatial cognitive ability.

A system and method for facilitating analysis of a wound in a target subject is provided. The method comprises obtaining one or more digital images of at least a portion of the wound; extracting a plurality of feature vectors from the one or more digital images; and identifying, using a first trained deep neural network, a type of wound tissue based on the plurality of extracted feature vectors.