A method, device and a computer program product for determining a training load distribution of a user is provided. Heart rate is continuously measured by a heart rate sensor. An aerobic training effect and load are calculated using intensity values and divided into categories of Aerobic Low and Aerobic High. An anaerobic training effect and load are calculated using determined characteristics related to high intensity periods of an exercise.

The present disclosure contains embodiments of an apparatus, system and method designed to facilitate learning or efficient multitasking involving movement while one or more user's or users' movement devices process or respond to different stimuli to facilitate users moving while learning, working, or participating in a simulation. In some embodiments this may be accomplished with the aid of a circular treadmill, spherical walkway, or combinable modular trackpads that may be linked to allow a user to lay the apparatus in a path suited for a plurality of environments. The embodiments of the disclosure involve the user moving while processing information (via: learning; creating through typing, moving, talking; or being entertained) and receiving feedback, assistance related to that movement, processing, or any combination thereof while combining the motion of the movement device with the feedback loop sent from sensor relays a user may receive an optimal experience for learning while moving.

Embodiments are disclosed for identifying poor cardio metabolic health using sensors of wearable devices. In an embodiment, a method comprises: obtaining estimates of maximal oxygen consumption of a user during exercise; determining at least one confidence weight based on context data; adjusting the maximal oxygen consumption estimates using the at least one confidence weight; aggregating the adjusted maximal oxygen consumption estimates to generate a summary maximal oxygen consumption estimate and corresponding confidence interval for the user; and classifying cardiorespiratory fitness of the user based on at least one of the summary maximum consumption estimate, the corresponding confidence interval, a population error model or a low cardiorespiratory fitness threshold.

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.

System and techniques for tracking caloric expenditure using sensor driven fingerprints are described herein. A set of outputs may be obtained from a plurality of sensors. A fingerprint may be generated using the set of outputs. The fingerprint may correspond to an activity observed by the plurality of sensors. The generated fingerprint may be compared to a set of fingerprints stored in a database. Each fingerprint of the set of fingerprints may correspond to a respective caloric expenditure. A caloric expenditure may be calculated for the activity based on the comparison. An exercise profile of a user may be updated using the caloric expenditure.

Systems and methods for positioning one or more sensors on a user. The system has user sensors, apparatus sensors, and treatment sensors. A processing device, executing computer readable instructions stored in a memory, cause the processing device to: generate an enhanced environment representative of an environment; receive apparatus data representative of a location of the apparatus in the environment; generate an apparatus avatar in the enhanced environment; receive user data representative of a location of the user in the environment; generate a user avatar in the enhanced environment; receive treatment data representative of one or more locations of the treatment sensors in the environment; generate, treatment sensor avatars in the enhanced environment; calculate a treatment location for each treatment sensor, wherein the treatment location is associated with an anatomical structure of a user; and generate instruction data representing an instruction for positioning the treatment sensors at the treatment location.

There is described an integrated unweighted gait training system having an unweighting system comprising a computer controller; a gait measurement system in communication with the controller; and a display in communication with the computer controller adapted and configured to provide real-time feedback to a user of the integrated unweighting gait training system. The unweighting system may be a differential air pressure (DAP) unweighting system or a non-DAP unweighting system.

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 disclosure relates to an apparatus and method for automatically adjusting an exercise prescription based on an exercise heart rate. The apparatus includes: a heart rate detection device, configured to detect a resting heart rate and a user's real-time exercise heart rate; an exercise movement library, configured to store various exercise instruction video and audio, and provide movement guidance for the user; an exercise guidance module, configured to retrieve and display movement video and audio from the exercise movement library to the user; and a central processing unit (CPU), configured to acquire the resting heart rate and the user's real-time exercise heart rate, calculate an effective exercise target heart rate range based on the resting heart rate, determine whether the real-time exercise heart rate falls within the effective exercise target heart rate range.

The present invention relates to a body carrier system for a mobile device, comprising a vest-like carrying element, a back part, two shoulder straps connected to the back part and a hip belt connected to the back part, and a two-part holding element for the mobile measuring device, whose both sub-elements can be reversibly fixed to the vest-like carrying element, as well as reversibly connected to each other, wherein each shoulder strap is equipped with welts in the front and/or wherein spaced welts are provided on the back part of the vest-like carrying element, and wherein on each of the two sub-elements of the two-part holding element welt guides are provided, so that the welt guides can be engaged with the welts.