Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, an alignment plan capable of enabling, during a treatment session, the aligning of a user's body. The method comprises generating machine learning models trained to identify alignment plans. The method also comprises receiving treatment data that comprises a first position of the user's body, aspects of a treatment plan, and one or more attributes of the user. The method further comprises generating the alignment plan by using the machine learning models. The generating is based on at least the aspects of the treatment plan and at least one of the one or more attributes of the user. The alignment plan may comprise a target position of the user's body and one or more elements for adjusting the user's body from the first position to the target position. The method also comprises transmitting the plan to a computing device.

A method for displaying archived exercise classes comprising displaying information about archived exercise classes that can be accessed by a first user via a computer network on a display screen at a first location, wherein the first user can select among a plurality of archived classes, outputting digital video and audio content comprising the selected archived class, detecting a performance parameter for the first user at a particular point in the selected class, displaying the performance parameter on the display screen, and displaying performance parameters from a second user at a second location on the display screen such that at least one of the performance parameters from the first user and at least one of the performance parameters from the second user at the same point in the class are presented for comparison.

A method includes providing a first video file to a plurality of exercise machines, the first video file including content associated with an exercise class. The method also includes receiving user data from the plurality of exercise machines, the user data including respective settings associated with a common performance metric. In such a method, the respective settings are used on the plurality of exercise machines during playback of a particular part of the first video file. The method also includes identifying a timestamp associated with the particular part of the first video file, and generating an executable control corresponding to the performance metric. The method further includes generating a second video file comprising the content and the executable control. In such methods, playback of the second video file causes display of the executable control at a part of the second video file corresponding to the timestamp.

An Internet of Thing (IoT) device includes a body with a processor, a camera and a wireless transceiver coupled to the processor.

Methods and systems are described for real-time instruction and coaching using a virtual assistant for interaction with a user. Users may receive feedback inferences provided generally in real-time after collection of video samples from the user device. Neural network architectures and layers may be used to determine motion patterns and temporal aspects of the video samples, as well as detect activities of the foreground user despite background noise. The methods and systems may have various capabilities, including but not limited to live feedback on performed exercise activities, exercise scoring, calorie estimation, and repetition counting.

A computer implemented method for consolidating and visually presenting information related to the physique of the user and their muscle training volume; specifically, tracking weight lifted per muscle group.

The present disclosure provides a method for performing a treatment plan, wherein the method comprises: receiving first patient data, wherein the first patient data includes at least a first patient identifier associated with the first patient and a first treatment plan; receiving second patient data, wherein the second patient data includes a second patient identifier associated with the second patient and a second treatment plan; receiving first measurement data associated with a first performance level of the first treatment plan by the first patient; receiving second measurement data associated with a second performance level of the second treatment plan by the second patient; determining differential data, wherein the determining is based on a contrast of the first or the second measurement data or first or second patient data; and generating, based on the differential data, an instruction to modify an operating state of the treatment apparatus.

Systems and methods for providing a distortion-free pool-surface display beneath a swimmer. In one embodiment, projectors are positioned below a water level at opposite walls of a pool, and are configured to project images to a display surface at the bottom of the pool beneath a swimmer. A camera is used to view images projected by the projectors and to provide corresponding image data to an image correction platform on a graphics processing unit (GPU). The image correction platform identifies distortions in the images, generates image corrections that counter the identified distortions, and applies the corrections to subsequently projected images. The image correction platform also generates image adjustment that cause overlapping portions of the projected images to match seamlessly. The projected images may provide immersive experiences, coaching/training interfaces or other interactive displays.

Systems and methods are for production, management, syndication and distribution of digital assets through a network such as the Internet or wireless network. Digital media assets are distributed to consumers through a syndicated network of Outlets under control of a central platform. Distribution is format agnostic. There is a single platform between the B2B2C, wherein a platform allows, through a single access for each stakeholder, the ability to each have control over availability dates and pricing specifications to a plurality of merchants and/or subscription outlets or channels. Subscription channels can support micro-subscriptions with diversely curated and priced offerings, including acceptance of crypto-currency. The delivered media assets may include content associated with an exercise apparatus, including content for an exercise session including computer generated content and computer augmented content created in response to exercise session data.

An exercise recommendation system determines recommended weights for users to perform exercises with. The exercise recommendation system accesses a plurality of exercise pairs, each labeled with performance statistics of users who performed the exercises. Each exercise in an exercise pair is associated with a weight. The exercise recommendation system trains a machine learning model on the plurality of exercise pairs to determine a weight to recommend to a user for a first exercise based on performance statistics of the user associated with one or more second exercises, which are each in an exercise pair with the first exercise. The exercise recommendation system retrieves performance statistics of a target user including weights for exercises previously performed by the target user. The exercise recommendation system applies the machine learning model to the performance statistics to determine a target weight to recommend and modifies a user interface to include the target weight.