Streaming analytics of human body movement data

Abstract

Large amounts of human body movement data may be collected, possibly via streaming data, from one or more sensors worn by a user. The data may be analyzed along with other classification data to generate feedback for the user or for other interested people (e.g., a trainer, a coach, a team member, health professional, etc.). The analysis may utilize one or more machine learning (ML) algorithms that use training data to create one or more ML models. When a user is evaluated after receiving feedback, accuracy of the feedback may be evaluated and fed back to the ML model to continue training the ML model(s).