An action management apparatus includes a bodily information measurement unit that measures bodily information, a communication unit for performing near-field wireless communication with another apparatus having a function of measuring bodily information, a bodily information acquisition unit that acquires the bodily information measured by the other apparatus included in a group along with the action management apparatus via a communication unit, and an information output unit that, based on first bodily information measured by the bodily information measurement unit and second bodily information acquired by the bodily information acquisition unit, outputs management information for managing an action of a wearer of an apparatus belonging to the group.

Athletic activity may be monitored using heart rate in addition to or instead of other types of metrics. Accordingly, multiple different activity types may be compared based on heart rate information. Additionally, the heart rate information may be visualized by displaying the heart rate data over time or relative to pace or distance. Additionally, the system may allow a user to analyze his or her heart rate performance by identifying one or more portions of the athletic activity in which a user exhibited a specified range of heart rates. Athletic activity sessions may further be tagged with various indicators including weather, terrain, difficulty and intensity. According to one or more aspects, data for different types of activity metrics may be polled and/or transmitted to a system at different rates or based on different schedules. Moreover, users may specify whether sensed data may be uploaded, recorded and/or visualized prior to or during an activity session.

A control system for controlling one or more of a plurality of exercise apparatuses across a network comprises a processor; a communication subsystem configured to communication with the plurality of exercise apparatuses across the network; and memory for storing information about one or more users. The information comprises, for each user, identity information, including a user identifier; and a resistance level indicator. Upon receipt of a user identifier from an exercise apparatus in the network, the processor is configured to identify the resistance level indicator stored in the memory corresponding to the user identifier, and cause the communication subsystem to transmit to the exercise apparatus the resistance level indicator for that user. Upon receipt of a performance parameter of a user from an exercise apparatus in the network, the processor is configured to determine whether or not to modify the resistance level indicator of that user stored in the memory based on the received performance parameter.

The present disclosure concerns determining physiological training effect of a physiological performance of a person by monitoring the performance using one or more performance-monitoring means in order to obtain performance data, and, according to one aspect of the invention, determining, using computing means capable of utilizing the performance data, a third training effect parameter describing a third physiological effect of the performance using a third determination method, the third physiological effect being a combination effect of the first and second physiological effects which are different from each other and are descriptive of different physiological effects of training, such as homeostatic disturbance and cumulative physiological load, respectively.

A system for biomechanical analysis of user posture and automatic customized manufacture of bicycle parts includes a servo-assisted simulator having a handlebar, a saddle, pedal cranks, and actuators, a device detecting input data that includes a 3D scanner for automatically detecting the position of body segments of the user and the angular ranges therebetween and generating three-dimensional physical data units, an electronic platform detecting pressure data of the user, a pair of insoles detecting plantar pressure, a computer connected to the actuators and to the detection device, a memory unit storing optimized initial data and instantaneous data, software comparing the optimized initial data and the instantaneous data and generating final data of the characteristics of the main parts, a spatial representation device spatially representing the final data, and a device for immediate manufacture of the parts using 3D printers. A method of biomechanical analysis and custom manufacture of bicycle parts.

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.

Computerized eyewear and corresponding methods measure a wearer's heart rate using a first optical sensor and a second optical sensor at least partially embedded in an eyewear temple. The first optical sensor transmits a first signal to a temple of the wearer and the second optical sensor transmits a second signal to the temple of the wearer. Reflections of the first signal are used to measure a raw heart rate delta and reflections of the second signal are used to measure a noise delta. The raw heart rate delta and the noise delta are used to determine a measured heart rate of the wearer of the computerized eyewear.

A biofeedback rehabilitation display for gait training visible to the subject including a plurality of foot placement targets visible to the subject on the display and moving along the display at a speed proportional to the desired gait speed of the subject and in a direction along the display representative of the direction of locomotion of the subject; a pair of subject foot icons visible to the subject illustrating real-time foot positioning of the subject throughout the gait pattern of the subject, wherein the foot icons distinguish between stance phase and swing phase throughout the gait pattern of the subject; and at least one real-time proximity measurement visible to the subject for each stance phase providing the subject with an indication of the proximity of each stance phase of each foot with an intended foot placement target.

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.

Motion activity data is collected from at least one sensor. An initial motion activity classifier function is applied to the motion activity data to produce an initial motion activity posteriorgram. Pre-processing and segmenting the motion activity data into windows produces segmented motion activity data from which sensor specific features are extracted. An updated motion activity classifier function is generated from the extracted sensor specific features. Subsequent motion activity data is also collected from the at least one sensor, and the updated motion activity classifier function is applied to the subsequent motion activity data to produce an updated motion activity posteriorgram.