A method includes receiving location data of a monitoring device when carried by a user and receiving motion data of the monitoring device. The motion data is associated with a time of occurrence and the location data. The method includes processing the received motion data to identify a group of the motion data having a substantially common characteristic and processing the location data for the group of the motion data. The group of motion data by way of processing the location data provides an activity identifier. The motion data includes metric data that identifies characteristics of the motion data. The method includes transferring the activity identifier and the characteristics of the motion data to a screen of a device for display. The activity identifier being a graphical user interface that receives an input for rendering more or less of the characteristics of the motion data.

The present invention relates to a device and method for monitoring vital signs of a subject. In particular, the device for monitoring vital signs comprises, an imaging unit for obtaining image data of said subject, an interface for receiving motion data of said subject and/or said imaging unit, a processing unit for extracting vital signs of said subject from said image data, and a control unit for adapting parameters of said imaging unit and/or said processing unit based on the received motion data. A further aspect of the invention relates to a fitness device comprising a device for monitoring vital signs and a motion detection unit for providing said device for monitoring vital signs with motion data.

Aspects relate to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

In one aspect, the present disclosure relates to a method including obtaining, by a fitness tracking device, a plurality of heart rate measurements of the user over a period of time, wherein the plurality of heart rate measurements can include heart rate data from a heart rate sensor of the fitness tracking device; analyzing, by the fitness tracking device, the plurality of heart rate measurements to determine a rate of change of a heart rate of the user during the period of time; determining, by the fitness tracking device, that the user is experiencing an onset phase if the rate of change of the heart rate during the period of time is greater than zero; determining, by the fitness tracking device, that the user is experiencing a cool-down phase if the rate of change of the heart rate during the period of time is less than zero; estimating, by the fitness tracking device, a first rate of energy expenditure of the user if the user is experiencing an onset phase using an onset calorimetry model; and estimating, by the fitness tracking device, a second rate of energy expenditure of the user if the user is experiencing a cool-down phase using a cool-down calorimetry model.

A method, apparatus, and a computer program for monitoring a fitness exercise are described. A plurality of heart-rate variability values and a plurality of exertion parameter values are measured during an exercise measured. The heart rate variability values correlate with the exertion parameter values through a human physiological mechanism, and the exertion parameter values characterize the physical exertion of the exercise. A mathematical correspondence is then constructed from the plurality of measured heart rate variability values and associated exertion parameter values. The mathematical correspondence describes correlation between the heart rate variability values and the exertion parameter values and the user's physiological state during the exercise. Then, the physical exertion of the exercise is monitored by applying the mathematical correspondence.

A device for determining and displaying a dose of a medicament to be administered to a user based, at least in part, on a measure of physical activity of the user described herein includes a determining unit configured determine a measure of physical activity of the user using information provided by one or more sensors. The device also includes a computer readable memory storing a set of predefined templates comprising predefined actions, rules, and parameters defining at least an initial medicament dose value, the measure of physical activity of the user, a time elapsed between an instance of physical activity and a current time, and a target blood glucose value, wherein the determining unit is further configured to determine the medicament dose based, at least in part, on the measure of physical activity of the user, by execution of one or more templates from the set of predefined templates.

The invention is directed to systems and methods that can determine a user's fitness based on a single factor such as oxygen lung volume (pmVO2). A heart rate measurement is conducted on the user after the user performs a physical test specified by a fitness application of the system. The heart rate measurement is converted into a pmVO2 value and compared to pmVO2 values of other individuals. The system assigns the user a fitness grade based on the comparison result. The system further includes an artificial intelligent system that helps the user to move from a grade to a higher grade.

A method of determining blood pressure measurements includes inflating a cuff, receiving an indication of pressure inside the cuff during inflation, determining a blood pressure based at least in part on the received indication, assigning a confidence level to the blood pressure, and determining whether the confidence level satisfies a threshold confidence level. Based at least on a determination that the confidence level satisfies a threshold confidence level, the method can include causing a display to display the blood pressure. Based at least on a determination that the confidence level does not satisfy a threshold confidence level, the method can include deflating the cuff, receiving an indication of pressure inside the cuff during deflation, determining another blood pressure, and causing a display to display a blood pressure.

A method includes receiving location data of a monitoring device when carried by a user and receiving motion data of the monitoring device. The motion data is associated with a time of occurrence and the location data. The method includes processing the received motion data to identify a group of the motion data having a substantially common characteristic and processing the location data for the group of the motion data. The group of motion data by way of processing the location data provides an activity identifier. The motion data includes metric data that identifies characteristics of the motion data. The method includes transferring the activity identifier and the characteristics of the motion data to a screen of a device for display. The activity identifier being a graphical user interface that receives an input for rendering more or less of the characteristics of the motion data.

Methods and apparatuses for athletic training optimization are disclosed. In one example, a fitness level change is identified. In one example, a current training intensity is updated to reflect an updated user fitness level.