Systems and methods are disclosed for generating and providing guided practices and coaching feedback (e.g., illustrated in 3D images, video, or audio) that allow golfers to follow along to improve their physical swing in a digital environment. The feedback may be provided with a 3D avatar 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 guided practices and coaching feedback.

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.

A training system operates to provide an online training system that includes an instructional portion, a performance portion and a results report. A trainer can create training modules and/or training programs and then launch a training program in which one or more users, utilizing a user system, can participate. A training program consists of one or more training modules. Each training module is configured to first run in a demonstration mode, in which the operator streams a demonstration of the physical activity required by the training module to one or more user systems. Users can thus view the demonstration of the physical activity on the user systems. The training module then enters a trial or trial mode in which each of the participants then engage in performing the physical activity. The user systems present a video/graphical display to show various performance criteria of the training module. The user systems also include a camera that is configured to monitor the activity of the user weighed against the performance criteria. Once the trial mode is completed, the data gathered by the user system cameras is then analyzed and evaluated and presented back to the participants.

Training at the proper level of effort is important for athletes whose objective is to achieve the best results in the least time. In running, for example, pace is often monitored. However, pace alone does not reveal specific issues with regard to running form, efficiency, or technique, much less inform how training should be modified to improve performance or fitness. A sensing system and wearable sensor platform described herein provide real-time feedback to a user/wearer of his power expenditure during an activity. In one example, the system includes an inertial measurement unit (IMU) for acquiring multi-axis motion data at a first sampling rate, and an orientation sensor to acquire orientation data at a second sampling rate that is varied based on the multi-axis motion data.

A system includes wearable devices positioned on a subject in different locations. Each wearable device includes motion sensors that measure the subject's movement in three dimensions. The motion sensors generate raw sensory data as the subject performs a physical movement. A data filter is selected based on a condition of the subject and a designated movement corresponding to the physical movement, and used to convert the raw sensory data into formatted data. A level of compliance of the physical movement with a movement model for the designated movement is determined by applying comparative modeling techniques to the formatted data and the movement model. Real-time feedback is delivered dynamically to the subject by the wearable devices during the performance of the physical movement based on the level of compliance. The movement model can be generated, and the comparative modeling techniques can be selected, based on the condition of the subject.

The present embodiments provide systems and methods for aggregating measurements captured by different technologies during a golf swing. By capturing measurements using different technologies, more accurate measurements may be provided to a user by selecting from the measurements, offsetting measurements based on the technologies used, and aligning measurements between devices. Further, by aggregating measurements received from different devices, additional features and functionality may be provided to the user that is absent from any one device used alone. Additionally, by storing the aggregated measurements, users, club fitters and instructors may access and leverage larger databases of measurements to better understand the user's golf swing and to provide better recommendations and instruction to the user.

A method includes causing display, during a first time period and via a first set of multiple smart mirrors, of live video depicting at least one user associated with the first set of multiple smart mirrors, without displaying a workout video. The method also includes causing display, during a second time period following and mutually exclusive of the first time period, and via a second set of multiple smart mirrors, of a workout video and a representation of at least one user associated with the second set of smart mirrors. The method also includes causing display, during a third time period following and mutually exclusive of the second time period, and via a third set of multiple smart mirrors, of live video depicting at least one user associated with the third set of multiple smart mirrors.

A method includes causing display, during a first time period and via a first set of multiple smart mirrors, of live video depicting at least one user associated with the first set of multiple smart mirrors, without displaying a workout video. The method also includes causing display, during a second time period following and mutually exclusive of the first time period, and via a second set of multiple smart mirrors, of a workout video and a representation of at least one user associated with the second set of smart mirrors. The method also includes causing display, during a third time period following and mutually exclusive of the second time period, and via a third set of multiple smart mirrors, of live video depicting at least one user associated with the third set of multiple smart mirrors.

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.

A metric device can facilitate the transmission of workout data to a mobile device within a data curation system. Ancillary features of the data curation system can ensure data accuracy associated with how much weight is or has been lifted, whether a user is actually performing an exercise, and/or if the user is performing the exercise properly. For example, determination of how many proper repetitions a user has actually performed can be based on a threshold value generated based on an averaging of the user's previous repetition data. The data received via the data curation system can be used for analysis and development such that the user can become more efficient and/or exercise caution during his/her workout.