An apparatus and a method for providing information are provided. The apparatus includes an interfacing unit configured to receive biometric information, which is measured by an external measuring device, corresponding to a health condition of a body part of a user, from the external measuring device; and a processor configured to determine a visual metaphor representation for characterizing a degree of the health condition based on mapping information between components of the visual metaphor representation and types of the received biometric information, and transform the received biometric information into the determined visual metaphor representation, where the interfacing unit is configured to transmit the transformed visual metaphor representation to an external displaying device.

The present disclosure generally relates to user interfaces for health applications. In some embodiments, exemplary user interfaces for managing health and safety features on an electronic device are described. In some embodiments, exemplary user interfaces for managing the setup of a health feature on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described. In some embodiments, exemplary user interfaces for managing a biometric measurement taken using an electronic device are described. In some embodiments, exemplary user interfaces for providing results for captured health information on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described.

A patient health management platform accesses a metabolic profile for a patient and biosignals recorded for the patient during a current time period comprising sensor data and/or lab test data collected for the patient. The platform receives patient data recorded during the current time period comprising food items consumed, medications taken, and symptoms experienced by the patient. The platform implements a machine-learned metabolic model to determine a metabolic state of the patient at a conclusion of the current time period by comparing a true representation of the metabolic state and a prediction of the metabolic state. The true representation and the prediction are determined based on the recorded biosignals and the recorded patient data, respectively. The platform generates a patient-specific treatment recommendation outlining instructions for the patient to improve their metabolic state and provides the patient-specific treatment recommendation to the patient device for display to the patient.

A system, method, and wireless earpieces for determining the status of the user. Sensor measurements of the user are performed utilizing a radar sensor of the wireless earpieces. The sensor measurements are analyzed. The status of the user is determined utilizing at least the sensor measurements of the radar sensor of the wireless earpieces. An alert is communicated to the user in response to there being a change in the status of the user.

Physiological signal processing systems include a photoplethysmograph (PPG) sensor that is configured to generate a physiological waveform, and an inertial sensor that is configured to generate a motion signal. A physiological metric extractor is configured to extract a physiological metric from the physiological waveform that is generated by the PPG sensor. The physiological metric extractor includes an averager that has an impulse response that is responsive to the strength of the motion signal. Related methods are also described.

Methods, systems and devices are provided for motion-activated display of messages on an activity monitoring device. In one embodiment, method for presenting a message on an activity monitoring device is provided, including the following method operations: downloading a plurality of messages to the device; detecting a stationary state of the device; detecting a movement of the device from the stationary state; in response to detecting the movement from the stationary state, selecting one of a plurality of messages, and displaying the selected message on the device.

Systems and methods for prompting a user to perform an exercise and monitoring the exercise are provided. Multiple independent sensors or sensor systems may be used to calculate energy expenditure. Various criteria may be used to manually or automatically select the independent sensor or sensor system or combination that will be used with the energy expenditure calculations.

A life management system receives data from a client device worn by a user, the data comprising biotelemetry data and activity data collected about a user wearing the client device. The life management system generates snapshot information using information from a group consisting of: the biotelemetry data, activity data, social data associated with the user, and user profile information associated with the user. The life management system generates a recommendation using portions of the snapshot information, and updates the snapshot information with the recommendation. The life management system executes a recommendation associated with the snapshot information in accordance with the user controls associated with the user.

A computer-implemented method for providing a real-time estimate of glycosylated hemoglobin (HbA1c) of a patient from a self-monitoring blood glucose (SMBG) measurement, and tracking changes in average glycemia of said patient over time is disclosed. The method includes the steps of; a computer computing a surrogate fasting measurement based on SMBG data received from the patient; a computer computing a glycation value using the said surrogate fasting measurement in a predetermined glycation equation; a computer outputting said glycation value as an initial estimate of HbA1c upon initialization of tracking of said patient's average glycemia; a computer updating said glycation value by using an updated SMBG value in said predetermined glycation equation, said updated SMBG value being based on a subsequent computed surrogate fasting measurement; and a computer computing an updated estimate of HbA1c using said initial estimate of HbA1c and said updated glycation value in a predetermined HbA1c estimation equation.

Systems and methods for monitoring food intake include an air pressure sensor for detecting ear canal deformation, according to some implementations. For example, the air pressure sensor detects a change in air pressure in the ear canal resulting from mandible movement. Other implementations include systems and methods for monitoring food intake that include a temporalis muscle activity sensor for detecting temporalis muscle activity, wherein at least a portion of the temporalis muscle activity sensor is coupled adjacent a temple portion of eyeglasses and disposed between the temple tip and the frame end piece. The temporalis muscle activity sensor may include an accelerometer, for example, for detecting movement of the temple portion due to mandibular movement from chewing.