The disclosed embodiments illustrate methods for recommending multimedia segments in multimedia content associated with online educational courses for annotation via a user interface. The method includes extracting one or more features associated with the multimedia content, wherein a feature of the one or more features corresponds to at least a requirement of an exemplary instance. The method further includes selecting a set of multimedia segments from one or more multimedia segments in the multimedia content, based on historical data that corresponds to interaction of one or more users with the multimedia content and the extracted one or more features associated with the multimedia content. Further, the method includes recommending the selected set of multimedia segments in the multimedia content through the user interface displayed on the user-computing device associated with a user, wherein the user annotates the recommended set of multimedia segments in the multimedia content.

A method executed by a computing device includes generating a virtual reality environment by detecting an illustrative asset common to first and second sets of assets. The method further includes rendering a three-dimensional (3-D) model of the illustrative asset and the first set of assets to produce 3-D frames of a first descriptive asset for issuance to a another computing device using an illustration approach. The method further includes rendering the three-dimensional (3-D) model of the illustrative asset and the second set of assets to produce 3-D frames of a second descriptive asset for issuance to the other computing device using an updated illustration approach.

Some embodiments of a virtual coaching platform can analyze user and coach characteristics to determine suggested coaching partnerships. Some virtual coaching platform embodiments can implement whole-person dimensionalities used to track progress and provide coaching resources and guidance. In some implementations, the virtual coaching platform can provide six whole-person dimensions including: centered, aware, agile, includes, elevates, and drives. Some virtual coaching platform embodiments can select a subset of the dimensionalities to update using determined associations between a user and the dimensionalities. Some virtual coaching platform embodiments can implement a motivational matrix to assess a user in a readiness versus clarity domain and provide coaching suggestions based on a corresponding type.

Some embodiments of a virtual coaching platform can analyze user and coach characteristics to determine suggested coaching partnerships. Some virtual coaching platform embodiments can implement whole-person dimensionalities used to track progress and provide coaching resources and guidance. In some implementations, the virtual coaching platform can provide six whole-person dimensions including: centered, aware, agile, includes, elevates, and drives. Some virtual coaching platform embodiments can select a subset of the dimensionalities to update using determined associations between a user and the dimensionalities. Some virtual coaching platform embodiments can implement a motivational matrix to assess a user in a readiness versus clarity domain and provide coaching suggestions based on a corresponding type.

A method includes capturing, using an Internet of Things (IoT) device, real-time video of a user performing an exercise associated with a first exercise class. Real-time video of the user is displayed, via a display, concurrently with video of an instructor, to provide a visual comparison of the user to the instructor. Image analysis of the real-time video of the user is performed to determine a performance of the user, and a representation thereof is displayed. Biometric data associated with the user is received at the IoT device from a wearable device at multiple points in time. Heart rates are identified based on the biometric data, and scores based on the heart rates are displayed via the display. A recommendation for a second exercise class different from the first exercise class is determined based on a profile of the user, and displayed via the display.

A method includes capturing, using an Internet of Things (IoT) device, real-time video of a user performing an exercise associated with a first exercise class. Real-time video of the user is displayed, via a display, concurrently with video of an instructor, to provide a visual comparison of the user to the instructor. Image analysis of the real-time video of the user is performed to determine a performance of the user, and a representation thereof is displayed. Biometric data associated with the user is received at the IoT device from a wearable device at multiple points in time. Heart rates are identified based on the biometric data, and scores based on the heart rates are displayed via the display. A recommendation for a second exercise class different from the first exercise class is determined based on a profile of the user, and displayed via the display.

A real-time virtual reality welding system including a programmable processor-based subsystem, a spatial tracker operatively connected to the programmable processor-based subsystem, at least one mock welding tool capable of being spatially tracked by the spatial tracker, and at least one display device operatively connected to the programmable processor-based subsystem. The system is capable of simulating, in virtual reality space, a weld puddle having real-time molten metal fluidity and heat dissipation characteristics. The system is further capable of importing data into the virtual reality welding system and analyzing the data to characterize a student welder's progress and to provide training.

A real-time virtual reality welding system including a programmable processor-based subsystem, a spatial tracker operatively connected to the programmable processor-based subsystem, at least one mock welding tool capable of being spatially tracked by the spatial tracker, and at least one display device operatively connected to the programmable processor-based subsystem. The system is capable of simulating, in virtual reality space, a weld puddle having real-time molten metal fluidity and heat dissipation characteristics. The system is further capable of importing data into the virtual reality welding system and analyzing the data to characterize a student welder's progress and to provide training.

Systems and methods for monitoring food intake include an air pressure sensor for detecting ear canal deformation, according to some implementations. For example, the air pressure sensor detects a change in air pressure in the ear canal resulting from mandible movement. Other implementations include systems and methods for monitoring food intake that include a temporalis muscle activity sensor for detecting temporalis muscle activity, wherein at least a portion of the temporalis muscle activity sensor is coupled adjacent a temple portion of eyeglasses and disposed between the temple tip and the frame end piece. The temporalis muscle activity sensor may include an accelerometer, for example, for detecting movement of the temple portion due to mandibular movement from chewing.

Systems and methods for monitoring food intake include an air pressure sensor for detecting ear canal deformation, according to some implementations. For example, the air pressure sensor detects a change in air pressure in the ear canal resulting from mandible movement. Other implementations include systems and methods for monitoring food intake that include a temporalis muscle activity sensor for detecting temporalis muscle activity, wherein at least a portion of the temporalis muscle activity sensor is coupled adjacent a temple portion of eyeglasses and disposed between the temple tip and the frame end piece. The temporalis muscle activity sensor may include an accelerometer, for example, for detecting movement of the temple portion due to mandibular movement from chewing.