Abstract: An avatar personalized for a subject and used in movement analysis and coaching uses a 3D polygon mesh representation of a human, authored for one human skeleton model, with a different size (scaled) skeleton model, without producing visual artifacts. Dimensions of the scaled skeleton model can be determined from three or eight measurements of a subject or from scanning or photographic methods. The avatar animated based on motion capture data may be animated alone or with one or more other avatars that are synchronized spatially, orientationally, and/or at multiple times to allow a user to easily compare differences between performances. An information presentation in an animation may use pixel energies from multiple animation frames to ensure that the information remains relatively stationary and does not obstruct important visual details.

Abstract: A protocol layer on top of the Bluetooth low energy (BLE) system of paired devices to provide transmission that allows arbitrary sizes of data to be sent. To guarantee transmissions, the transmissions may be validated and, if required, resent to replace data that was lost or corrupted. The protocol layer also supports Remote Procedure Calls to allow functions on either of two connected devices to be executed on one device on behalf of the other. A further protocol layer also allows high priority, short messages to temporarily interrupt the transmission of low priority, long messages.

Abstract: Described herein are to frameworks and methodologies configured to enable real-time adaptive delivery of skills training data based on monitoring of user performance data. Embodiments of the invention have been particularly to enable real-time control over a performance instruction user interface (for example in terms of rate), and/or control over delivery of media data (for example in terms of rate and/or pan/zoom position).

Abstract: The present application relates generally to managing media. In some embodiments, time-coded skill performance event data is derived from end-user hardware including a plurality of Motion Sensor Units (MSUs), such as a MSU-enabled garment. Data derived from the MSUs is processed to identify performance events representative of specific predefined physical motion-based skills. This allows automated categorisation and/or identification of video data responsive to presence of particular skills that have been performed and captured.

Abstract: The present invention relates to delivery of content that is driven by input from one or more performance sensor units, such as performance sensor units configured to monitor motion-based performances and/or audio-based performances. Embodiments of the invention include software and hardware, and associated methodologies, associated with the generation, distribution, and execution of such content. Attention is paid to implementations whereby performance sensor units provide input to an adaptive training program.

Abstract: The application relates to technological frameworks whereby user skill performances are monitored using Performance Sensor Units (PSUs), and data derived from those PSUs is processed thereby to determine attributes of the user skill performances. For example, the identification of attributes of performances is used to drive computer processes, such as computer processes described herein. Particular focus is given to technologies which enable the gamification of skills via delivery of competitive challenges, such challenges being driven by data derived from PSUs that monitor physical performances. For example, in one embodiment users compete in the context of performing a particular skill or skills “better” than others (for example in the context of amplitude, power, accuracy, successive completions, and so on).