METHODS AND APPARATUS FOR ACTIONS, ACTIVITIES AND TASKS CLASSIFICATIONS BASED ON MACHINE LEARNING TECHNIQUES

摘要

Systems and methods of the present disclosure enable automated recognition of user performed activities and tasks using sensor data by receiving raw sensor data while a user performs a series of activities wearing at least one sensor for a predetermined interval of time. The raw sensor data is converted into a set of feature values. An action recognition machine learning model is used to generate action labels indicative of actions performed by the user during the predetermined interval of time based on trained action model parameters and the set of feature values. A task recognition machine learning model is used to generate task labels indicative of tasks performed by the user during the predetermined interval of time based on trained task model parameters, the set of action labels and the set of feature values, and a message is displayed with an indication of the task labels to a user.