An approach for providing real-time feedback during a sports activity (e.g., golf play) based, at least in part, on analysis of sensor information, is disclosed. The approach involves receiving sensor data associated with one or more sensors arranged to track playing technique information of a player engaged in a sports activity. The approach also involves processing the sensor data in real-time to determine the playing technique information. The approach further involves retrieving baseline information for the player. The approach also involves comparing the playing technique information with the baseline information. The approach further involves generating, in real-time with the engagement of the sports activity, an instructional message to modify playing technique of the player based on the comparison. The approach also involves initiating presentation, during the sports activity, of the instructional message to a user interface of a device accessible by the player.

Aspects are directed to visual support for exercise compliance including capturing, via a camera of a user device, images of a first person performing one or more motions. Previously recorded images of a second person performing the one or more motions are accessed via the user device. Combined images are created by overlaying the images of the first person performing the one or more motions on the images of the second person performing the one or more motions. The combined images are output via a display device.

A social engagement system includes a first exercise machine having a display able to present videos, a three-dimensional camera system, and local processing system able to provide pose estimation based on data from the three-dimensional camera system. The system also includes a communication module for connection to a cloud processing system, with the cloud processing system supporting connection to a second exercise machine having a display able to present videos, a three-dimensional camera system, and local processing system able to provide pose estimation based on data from the three-dimensional camera system. Additionally, the connection allows transfer of data useful for social engagement.

A method for recommending golf-related contents is provided. The method includes detecting at least one body part of a user from a captured image by using an artificial neural network model, when the captured image related to the golf swing of the user is acquired; estimating at least one problem about the golf swing of the user by referring to the position of the detected at least one body part; and deriving, in reference to information related to the problem associated with the golf-related contents, at least one piece of candidate content associated with the at least one problem from among golf-related contents.

Apparatus, systems, and methods are provided for measuring and analyzing movements of a body and for communicating information related to such body movements over a network. In certain embodiments, a system gathers biometric and biomechanical data relating to positions, orientations, and movements of various body parts of a user performed during sports activities, physical rehabilitation, or military or law enforcement activities. The biometric and biomechanical data can be communicated to a local and/or remote interface, which uses digital performance assessment tools to provide a performance evaluation to the user. The performance evaluation may include a graphical representation (e.g., a video), statistical information, and/or a comparison to another user and/or instructor. In some embodiments, the biometric and biomechanical data is communicated wirelessly to one or more devices including a processor, display, and/or data storage medium for further analysis, archiving, and data mining. In some embodiments, the device includes a cellular telephone.

Systems and methods of analyzing a user's motion during a swimming session are described. One or more motions sensors can collect motion data of the user. A processor circuit can make motion analysis based on the motion data. The processor circuit can determine if the user's arm swing is a genuine swim stroke. The processor circuit can also determine whether the user is swimming or turning. The processor circuit can also classify the user's swim stroke style. The processor circuit can also determine the user's swim stroke phase. The processor circuit can also determine the user's stroke orbit consistency.

An interactive exercise system includes a mechanical support system and a display module held by the mechanical support system. A force-controlled motor is attached to the mechanical support system and a reel is driven by the force-controlled motor. The interactive exercise system also has a handle graspable by a user and includes a cord extending between the reel and the handle. Force applied through the force-controlled motor is based at least in part on detected user force input.

A computer-implemented method includes extracting movement data from a video of a user and identifying a movement type by providing the movement data to a classifier. The classifier is trained using data including bodily locations for multiple movement types including the movement type associated with the movement data. The method further includes comparing the movement data to target movement data for the movement type and providing feedback to the user based on the comparison between the movement data and the target movement data.

An interactive AI coaching-based musculoskeletal exercise and rehabilitation training system, includes: a user state information measurement unit connected to a cloud server through a wired or wireless network and measuring state information, the state information being information about a user's exercise posture or physical condition; a display panel displaying necessary information to a user during exercise based on the state information measured by the user state information measurement unit; an exercise unit allowing a user to perform a resistance exercise or a balance exercise; a coaching engine receiving and analyzing the state information measured by the user state information measurement unit during a user's exercise using the exercise unit and providing AI-based interactive coaching information to a user through the display panel; and an expert terminal providing rehabilitation service information to a user exercising using the exercise unit through the display panel in parallel with the coaching engine.

A system and method is disclosed for a surround-perspective motion annotation comprising: an image/video input for capturing and/or parsing into at least one image frame of a subject performing at least one motion from each of at least three perspectives; a vector generating module for generating a test vector or wire mesh corresponding to a pose of the subject in each of the captured/parsed frame from each of the perspectives; and an annotation module for inputting a drawing imposed on the test vector/mesh for a visual contrast against any one of a feature from the test vector/mesh from any one of the perspectives. Further disclosed embodiments include for a system and method for generating multi-perspective, color-coded deviations of a subject from a reference (color wheel). Further embodiments include for a system and method for generating an optimal motion signature (OMS) for the subject based on his or her generated color wheel.