Filtering of Multimodal Motion Capture Data through Individualized Musculoskeletal Human Models (C02)

• Subject Area: Biomedical Systems Technology
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 442419336

A novel method for correcting and filtering of multimodal motion capture data in conjunction with correspondingly necessary multi-domain modelling of musculoskeletal fullbody human models is being researched. Based on the individualized human models, kinematic respectively dynamic tracking algorithms are investigated, which can be applied to different combinations of multimodal measurement data. Furthermore, the new methods are tested, evaluated and benchmarked to conventional methods. New EmpkinS measurement techniques will be transferred to the newly established methods as soon as available.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1483: Empathokinaesthetic Sensor Technology – Sensor Techniques and Data Analysis Methods for Empathokinaesthetic Modeling and Condition monitoring
• Applicant Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg
• Project Heads: Dr.-Ing. Jörg Miehling; Professor Dr.-Ing. Sandro Wartzack