Supervised Machine Learning Applied to Inertial Measuring Unit Data for Technique Analysis in Team and Individual Swing Sports

The developments in the field of sports activity recognition and performance analysis research have been expedited by the advances in motion analysis technologies for data acquisition (Richter et al., 2021). During the time that these technologies were developed and inversely applied, there were coupled advancements in machine learning algorithms for data extraction and analysis. Machine learning is the study of computationally intelligent algorithms which extract unique features from data and identify patterns of interest without the need for explicit programming. The purpose of this study is to give an overview of the current state of the application of supervised machine learning techniques for the recognition and classification of sports motion for technique evaluation in team and individual swing sports.