Academic staff
Leonie Laskowitz
Research focuses on motion capture technology
News
Podcast and article feature in “Fokus Orange” at the Technical University of Applied Sciences Würzburg-Schweinfurt (THWS)
In the latest issue of Fokus Orange by the Technical University of Applied Sciences Würzburg-Schweinfurt (THWS), I provide insights into my research. The feature focuses on the new Doctoral Center for Sustainable and Intelligent Systems (NISys) and the opportunities it creates for doctoral researchers at universities of applied sciences.
Dokument(e)
Fokus Orange.png Interview.JPGPresentation of the Doctoral Research Project at the NISys Doctoral Retreat
At this year’s doctoral retreat of the Doctoral Center for Sustainable and Intelligent Systems (NISys), more than 90 doctoral projects were presented. My research contribution focuses on combining virtual reality and motion capture for high-resolution analysis of human movement in rehabilitation. Building on this, I develop a framework that translates selected movement indicators into structured feedback strategies to support sustainable motor learning and transfer beyond the virtual environment.
Dokument(e)
NISys_Vortrag.jpeg NISys.jpegProjects
Martial arts training with technical support
Through kinematic motion analysis using motion capture technology, the training of beginners in the martial art of Muay Thai was analyzed and optimized. Traditionally, the movement sequence is guided and evaluated by a trainer. However, in cooperation with the university, athletes did not train in a dojo but in the motion capture lab at Sanderheinrichsleitenweg. This allowed for very detailed control over the movement sequences and possible sources of error could be corrected early on.
For more information, visit: www.mainpost.de/regional/wuerzburg/kampfsport-training-mit-technischer-unterstuetzung-art-11034350"
Dokument(e)
Foto L. Laskowitz | Messung der Muay Thai Technik mittels MoCap Skelett.webpEvaluation of a Motion Capture Training Approach as an Indicator for Performance Improvement in Muay Thai
A study at the Technische Hochschule Würzburg-Schweinfurt investigated the use of Motion Capture (MoCap) in the martial art of Muay Thai. Muay Thai required precise movements that were previously time-consuming and subjectively evaluated. The study combined MoCap with traditional training methods to enhance athletes' performance, demonstrating significant progress.
For more information, visit:
www.thws.de/service/news-presse/pressemeldungen/thema/evaluation-eines-motion-capture-trainingsansatzes-als-indikator-zur-leistungssteigerung-im-muay-thai/
www.linkedin.com/posts/leonie-laskowitz_wilkommen-kaeuppele-festung-activity-6991408408348307456-teJP
Dokument(e)
Leonie-Laskowitz-und-zwei-Athleten_-deren-Bewegungsabläufe-mithilfe-Motion-Capture-und-einer-Visual.webpPublications
Buchbeiträge & Journals
Laskowitz, L., Huffstadt, K. & Müller, N. H. (2026)
Enhancing Immersion in Virtual Reality Martial Arts Training: Toward Realistic and Practical Applications. In: Virtual Worlds 2026, 5(1), 11.
Laskowitz, L., Huffstadt, K. (2025)
Conceptual Design of an Immersive VR Training System with Real-Time Motion Capture for Sports and Therapy. In: ICHMI 2025, The 5th International Conference on Human–Machine Interaction, pp. 57-63
Laskowitz, L. & Müller, N. H. (2024)
Training Development in Dance: Enhancing Precision Through Motion Capture and a Virtual Environment for Injury Prevention. In: Proceedings of HCII 2024, The 11th International Conference in Learning and Collaboration Technologies, pp. 125-137.
Laskowitz, L. & Müller, N. H. (2023)
Introduction and Evaluation of an Alternative Training Approach as Indicator of Performance Improvement in Martial Arts with the Help of Kinematic Motion Analysis Using Motion Capture. In: Proceedings of ACHI 2023, The Sixteenth International Conference on Advances in Computer-Human Interactions, pp. 152-158.
Laskowitz, L., Huffstadt, K. (2023)
Between Reality and Fiction: Self-Representation as an Avatar and Its Effects on Self-Presence. In: Proceedings of the 2023 International Joint Conference on Robotics and Artificial Intelligence, pp. 193-203.