JumpXClass: Explainable AI for Jump Classification in Trampoline Sports

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review



Movement patterns in trampoline gymnastics have become faster and more complex with the increase in the athletes’ capabilities. This makes the assessment of jump type, pose, and quality during training or competitions by humans very difficult or even impossible. To counteract this development, data-driven solutions are thought to be a solution to improve training. In recent work, sensor measurements and machine learning is used to automatically predict jumps and give feedback to the athletes and trainers. However, machine learning models, and especially neural networks, are black boxes most of the time. Therefore, the athletes and trainers cannot gain any insights about the jump from the machine learning-based jump classification. To better understand the jump execution during training, we propose JumpXClass: a tool for automatic machine learning-based jump classification with explainable artificial intelligence. Using elements of explainable artificial intelligence can improve the training experience for athletes and trainers. This work will demonstrate a live system capable to classify and explain jumps from trampoline athletes.


Original languageEnglish
Title of host publicationDatenbanksysteme fur Business, Technologie und Web, BTW 2023
EditorsBirgitta Konig-Ries, Stefanie Scherzinger, Wolfgang Lehner, Gottfried Vossen
PublisherGesellschaft fur Informatik (GI)
Number of pages6
ISBN (electronic)9783885797258
Publication statusPublished - 6 Mar 2023

External IDs

Scopus 85149960459
dblp conf/btw/WoltmannFHL23
Mendeley b8564364-7ffb-3b2d-9a60-981793e061b5
ORCID /0000-0001-8107-2775/work/142253564


Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards

Subject groups, research areas, subject areas according to Destatis

ASJC Scopus subject areas


  • applied AI, explainable AI, machine learning, sports, trampoline