Second Place in ISEA Competition: Running Surfaces Analysed with AI

A student at the University of Applied Sciences Technikum Wien was awarded 2nd place in the International Sports Engineering Association’s (ISEA) latest project competition: Johannes Hafergut (Master’s programme Sports Technology) developed a machine learning model that recognises different running surfaces based on raw data from an acceleration sensor. The K-Nearest-Neighbour algorithm (KNN) was selected with an accuracy of 86.4% because it best suited the project requirements. The model could be used in sports science and wearables to investigate correlations between running surfaces and injury risks.

This is the fourth year in a row that a student from the UAS Technikum Wien has achieved a place on the podium in this competition. The project was developed in the Machine Learning course by Otto Hofstätter, in the Sports Engineering, Biomechanics & Ergonomics field of expertise. This year, a student from Stanford University took first place, with a student from the Technical University of Munich taking third place.

Further Links:

Master’s Degree in Sports Technology – UAS Technikum Wien

Competence Field Sports Engineering, Biomechanics & Ergonomics – UAS Technikum Wien

Department Life Science Engineering – UAS Technikum Wien

Project competition 2024 of the International Sports Engineering Association (ISEA)

Students achieve a ‘hat-trick’ in the International Sports Engineering Association competition (December 2022)

Interdisciplinary knowledge as a success factor: sports technology student wins international competition with ballet project (March 2022)