Patent ID: 11797602

Abstract:
An editor application configured for setting up at least one evaluation data structure, each evaluation data structure being configured for evaluating a corresponding specific motion pattern in a sequence of image data structures Each evaluation data structure includes a machine learning (ML) model artifact of an exercise specific ML model configured for evaluating the particular physical exercise. Further, the ML model is trained based on a plurality of sequences of image data structures showing different variants of the specific motion pattern for the particular physical exercise, and for each image data structure, a set of key data elements is provided, a key data element indicating a respective position of a landmark in the image data structure, said training being further based on class labels provided for each image data structure. In addition, the ML model is configured to determine, based on input data comprising key data elements provided for at least one image data structure, class labels for each image data structure, said class labels identifying at least one of: at least one motion phase of the specific motion pattern, at least one evaluation point of the specific motion pattern, wherein the key data elements indicate positions of landmarks in the image data structures; generate geometric evaluation data and perform a geometric evaluation of a configuration of key data elements of a particular image data structure that corresponds to an evaluation point or for performing a geometric evaluation of at least one motion phase of the specific motion pattern; and generate feedback data for providing a feedback to the user, said feedback depending on the result of the geometric evaluation. Further, the editor application comprises at least one graphical user interface, the graphical user interface being configured for accepting user input for training the ML model underlying the ML model artefact.