The aim of this Thesis is to create a framework that employs Machine-Learning algorithms to automatically assess proficiency in the practice of Tai Chi Chuan by analyzing video recordings and extracting information through Human Pose Estimation. Tai Chi is a form of low-impact mind-body exercise characterized by slow and fluid movements and whose positive impacts on health, particularly in relation to balance, have been analyzed by numerous studies. The data employed to achieve the goal of this Thesis was collected from thirty-two older adults aged between 65 and 85 years who were asked to perform six different Tai Chi exercises chosen in collaboration with Tai Chi experts.