Subproject B04
Subproject B04
Visualization of Motion Sequences Based on a Biomechanical Model
Subproject B04 is a significant component of EmpkinS research, with a primary focus on improving the visualization of recorded movement sequences obtained from empathokinesthetic sensors or biomechanical simulations. Its goal is to enhance medical interpretation and diagnosis by developing methods to make complex motion data more understandable and clinically valuable.
At its core, this subproject aims to create visualization techniques that improve the comprehensibility of movement sequences and help extract meaningful information for medical professionals. Various empathokinesthetic sensors and biomechanical simulations bridge the gap between raw data and clinical insights. The research in
B04 has the potential to enhance the medical community’s ability to interpret and diagnose conditions related to human motion, contributing to data-driven healthcare advancements.
Contacts
Prof. Dr.-Ing. Marc Stamminger
Principal Investigator
Prof. Dr. med. Jürgen Winkler
Principal Investigator
Daniel Zieger, M. Sc.
Doctoral Canidate
Jann-Ole Henningson, M. Sc.
Associated Doctoral Candidate
Prof. Dr. Bernhard Egger
Associated Member
PD Dr. Heiko Gaßner
Associated Member
Prof. Dr. Jochen Klucken
Associated Member
Additional Information
- Nguyen DT., Zieger D., Gambietz M., Koelewijn A., Stamminger M., Kaup A.:
Multiresolution point cloud compression for real-time visualization and streaming of large 3D datasets. Asilomar Conferense on Signals, Systems, and Computers (2024)
A Wireless Joint Communication and Localization EMG-Sensing Concept for Movement Disorder Assessment. IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology (2023), S. 1-10. ISSN: 2469-7249. DOI: 10.1109/JERM.2023.3321974
, , , , , , , , , , :- Henningson JO., Semmler M., Döllinger M., Stamminger M.:
Joint Segmentation and Sub-pixel Localization in Structured Light Laryngoscopy. 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). DOI: 10.1007/978-3-031-43987-2_4 - Wirth V., Liphardt AM., Coppers B., Bräunig J., Heinrich S., Leyendecker S., Kleyer A., Schett G., Vossiek M., Egger B., Stamminger M.:
ShaRPy: Shape Reconstruction and Hand Pose Estimation from RGB-D with Uncertainty. Proceedings of the IEEE/CVF International Conference on Computer Vision (Paris, 2023)