This invention is used to control the duration of time it takes to charge any device, depending on how many units the user has taken out of their fitness goal. This invention connects to a fitness device such as a smart watch and retrieves the amount of units the user has completed. Being conditional on how many units the user has taken, the device will either charge at a normal pace or proportionally slower. For example, if the user's daily goal was 10,000 units and they completed 5,000 units, their device would charge half its normal pace. This invention charges the device more slowly by pausing the charges for periods of time.

A method for displaying archived exercise classes comprising displaying information about archived exercise classes that can be accessed by a first user via a computer network on a display screen at a first location, wherein the first user can select among a plurality of archived classes, outputting digital video and audio content comprising the selected archived class, detecting a performance parameter for the first user at a particular point in the selected class, displaying the performance parameter on the display screen, and displaying performance parameters from a second user at a second location on the display screen such that at least one of the performance parameters from the first user and at least one of the performance parameters from the second user at the same point in the class are presented for comparison.

A method includes providing a first video file to a plurality of exercise machines, the first video file including content associated with an exercise class. The method also includes receiving user data from the plurality of exercise machines, the user data including respective settings associated with a common performance metric. In such a method, the respective settings are used on the plurality of exercise machines during playback of a particular part of the first video file. The method also includes identifying a timestamp associated with the particular part of the first video file, and generating an executable control corresponding to the performance metric. The method further includes generating a second video file comprising the content and the executable control. In such methods, playback of the second video file causes display of the executable control at a part of the second video file corresponding to the timestamp.

Methods and systems are described for real-time instruction and coaching using a virtual assistant for interaction with a user. Users may receive feedback inferences provided generally in real-time after collection of video samples from the user device. Neural network architectures and layers may be used to determine motion patterns and temporal aspects of the video samples, as well as detect activities of the foreground user despite background noise. The methods and systems may have various capabilities, including but not limited to live feedback on performed exercise activities, exercise scoring, calorie estimation, and repetition counting.

A system for monitoring the symmetry of a lifting stance, the system including: a platform for supporting a weightlifter during a lift, the platform including support plates which include load sensors; a processor in data communication with the one or more load sensors for receiving and processing weightlifter load data, the processor configured to assess weightlifter symmetry data against a symmetry threshold to provide a symmetry result; and an output module for informing the weightlifter of the symmetry result. Also described is a method for monitoring the symmetry of a lifting stance, including the steps of: receiving data from one or more load sensors on one or more support plates on a weightlifting platform to process weightlifter load data; processing weightlifter load data to provide weightlifter symmetry data; assessing weightlifter symmetry data against a symmetry threshold to provide symmetry result data; and displaying the symmetry result data.

A method for providing exercise load information of a target entity is provided. The method includes obtaining a target data set of the target entity for a target exercise session including a plurality of time units, wherein the target data set includes a sequence of kinematic information of the target entity for each of the plurality of time units; and determining, based on the target data set, an estimated load index reflecting a level of exercise load of the target entity for the target exercise session using an artificial neural network (ANN).

A system for motion analysis includes a sensing device positioned at a knee joint of a bicycle rider, and an electronic device in communication with the sensing device. The electronic device is configured to receive, from the sensing device, a series of pieces of sensed data representing orientations of the sensing device at different times, to determine a motion trajectory of a knee of the rider based on the received pieces of sensed data, and to generate an estimation result regarding correctness of a riding posture of the rider based on the motion trajectory.

There is disclosed a system for conducting multi-member group competitions involving physical exertion, the system includes a competition server that serves to designate a set of parameters for a competition involving at least two competing groups of individuals engaged in physical activity, the set of parameters defining a win condition requiring physical activity to be completed by at least two separate individuals within each group. The system further receives data representative of physical activity of multiple individuals in a first group, receives data representative of physical activity of multiple individuals in a second group, determines whether the win condition has been satisfied by the first group or the second group, and identifies a winner as the first group or the second group that completed the win condition.

Systems and methods are for production, management, syndication and distribution of digital assets through a network such as the Internet or wireless network. Digital media assets are distributed to consumers through a syndicated network of Outlets under control of a central platform. Distribution is format agnostic. There is a single platform between the B2B2C, wherein a platform allows, through a single access for each stakeholder, the ability to each have control over availability dates and pricing specifications to a plurality of merchants and/or subscription outlets or channels. Subscription channels can support micro-subscriptions with diversely curated and priced offerings, including acceptance of crypto-currency. The delivered media assets may include content associated with an exercise apparatus, including content for an exercise session including computer generated content and computer augmented content created in response to exercise session data.

Disclosed is an exercise posture correction assistance method using working muscle information depending on motion performed by at least one server, including acquiring first image information containing movement of a user corresponding to a specific practice motion from a user terminal, deriving skeleton information corresponding to the movement of the user based on the first image information, generating second image information by indicating the movement of the user using a skeleton shape based on the first image information and the skeleton information, deriving muscle information corresponding to the specific practice motion from a database, generating muscle movement image information corresponding to the movement of the user based on the skeleton information and the muscle information, and providing the second image information and the muscle movement image information to the user terminal.