Classifying action correctness in physical rehabilitation exercises

Abstract

The work in this paper focuses on the role of machine learning in assessing the correctness of a human motion or action. This task proves to be more challenging than the gesture and action recognition ones. We will demonstrate, through a set of experiments on a recent dataset, that machine learning algorithms can produce good results for certain actions, but can also fall into the trap of classifying an incorrect execution of an action as a correct execution of another action.

IJCAI 2018, ARIAL workshop, 2nd Workshop on AI for Aging, Rehabilitation and Independent Assisted Living