rowAIng kinematics

Project duration: 01/2026 – 12/2027

Rowing is a demanding sport that requires strength, endurance and precise technique. In elite sport in particular, the focus is therefore on optimising both individual and team-oriented rowing technique. Currently, technique assessment is based on kinematic and dynamometric measurements taken from the rowing machine, as well as on coaches’ subjective evaluation of body movements. This results in a significant shortfall in the comprehensive recording and quantification of performance losses caused by incorrect body movements.

As part of this application project funded by the BISp, machine learning (ML) methods are therefore being employed, optimised and integrated to reliably and precisely capture athletes’ body movements whilst rowing using video recordings. Building on this data, algorithms are also being developed to detect and quantify errors in technique execution. In this context, the focus is both on assessing the temporal sequence of individual movements and on determining the degree of synchronisation within a crew boat.

These developments are intended to close a significant gap in the analysis and optimisation of rowing technique, thereby making a major contribution to improving performance in rowing. Furthermore, the results are also intended to be used for injury prevention.