A fitness system includes a computing system in communication with a wearable device and multiple pieces of exercise equipment. The wearable device is associated with a user, includes a user sensor for detecting motion, and outputs user sensor data. The multiple pieces of exercise equipment are configured to be used by the user to perform an exercise therewith, include an equipment sensor for detecting motion, and output equipment sensor data. The computing system receives and processes the user sensor data collected at a first time and the equipment sensor data collected from the multiple pieces of exercise equipment at the first time to associate the user with one of the multiple pieces of exercise equipment used by the user at the first time, determines exercise information, exercise recommendations, or both, and transmits the exercise information, the exercise recommendations, or both.

An exercise analysis device includes: a group classification unit that classifies activity data, as which measurement data associated with an exercise motion is recorded together with certain reference data that changes during exercise, into multiple groups based on the reference data; a representative data generating unit that generates representative data for the activity data in each of the multiple groups; and a tendency analysis unit that analyzes a tendency of the representative data with respect to the reference data in the multiple groups. With the exercise analysis device, exercise motions can be analyzed appropriately in consideration of the tendency of the entire exercise.

An electronic apparatus is provided. The electronic apparatus may include a display; a camera; a memory in which reference information associated with a content that provides information is stored; and a processor may be configured to obtain an image photographing a user through the camera while the content is provided through the display; obtain context information associated with the user based on the image; identify an execution status of the user associated with the information provided by the content by comparing the obtained context information and the reference information; and control an output state of the content based on the execution status of the user.

Systems and methods are disclosed for generating a 3D avatar and object fitting recommendations using a biomechanical analysis of observed actions with a focus on representing actions through computer-generated 3D avatars. Physical quantities of biomechanical actions can be measured from the observations, and the system can analyze these values, compare them to target or optimal values, and use the observations and known biomechanical capabilities to generate the 3D avatars and object fitting recommendations.

Performance information associated with a previous repetition of an exercise movement is received. Performance of one or more upcoming repetitions is predicted, based at least in part on the performance information associated with the previous repetition of the exercise movement. A failure classification of whether the one or more upcoming repetitions is associated with an occurrence of physical failure is performed, based at least in part on the predicted performance of the one or more upcoming repetitions of the exercise movement. A number of repetitions in reserve is determined, based at least in part on the failure classification.

A method of predicting the likelihood of a post T-off golf swing or consecutive swings resulting in a ball being sunk in a hole; the method utilizing communication equipped cameras or communication equipped laser rangefinders at known locations to determine accurate ball lie information. Transmission of this location information in real time to a processing facility linked to a database of historical play information incorporating at least ball position information and golf course in order to calculate odds of success of the upcoming swing and/or subsequent swings.

A method for optimizing at least one exercise is provided. The method includes receiving user data. The user data includes biometric attribute data associated with a user of an exercise device. The method includes generating at least one interval, the at least one interval including at least duration data and target power data each associated with the exercise. The method includes during the at least one interval, receiving measurement data associated with at least one of the user and the exercise device. The method includes calculating, based on the measurement data and the user data, energy data associated with an expended energy of the user during the at least one interval, the energy data including quantity data and source information each associated with at least one energy source. The method includes generating, via an artificial intelligence engine, a machine learning model trained to identify the at least one energy source.

A method, comprising providing playback of one or more sets of three dimensional positional data of a subject performing an activity; detecting input from an editor respective to the playback of the one or more sets of three dimensional positional data; and storing parameters of the activity based on the detected input in an activity profile for use in movement based instruction.

According to various embodiments, an electronic device may comprise: a communication module comprising communication circuitry configured to communicate with at least one external electronic device; a memory for storing at least one app; and a processor operatively connected to the communication module and the memory. The processor may be configured to: activate a workout management app (e.g., home gym app) stored in the memory; in response to the execution of the at least one app, identify whether a workout-related content has been executed on the basis of the activated workout management app; display an object for execution of a training program through the workout management app based on the workout-related content being executed; in response to a user input on the object, make an automatic connection with the at least one external electronic device through the communication module; configure, on the basis of at least one piece of workout-related information acquired from the at least one external electronic device, a training program screen into which the workout-related content and the workout-related information are integrated; and display the training program screen through the at least one external electronic device.

In one embodiment, a method includes accessing, by one or more computing devices, user sensor data from one or more wearable sensors on one or more players and optical sensor data from one or more cameras, where the user sensor data includes location data of the player and acceleration data, and where the optical sensor data includes several frames portraying the players and several scenes from an athletic event. The one or more computing devices analyzes, using a machine-learning model, the optical sensor data to identify the players and one or more actions during the athletic event and calculates one or more player metrics for the players based on the user sensor data and the identified actions. The one or more computing devices normalizes the player metrics for the players based on one or more weighted parameters and provides a report to one or more users.