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Institute of Applied Dynamics

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  4. motion capturing

motion capturing

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    • multibody dynamics and robotics
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motion capturing

Motion Capture technologies are used to record the positions of multibody, especially biomechanical, systems which form as inputs at various levels to improve the simulation quality. The recorded motion can be used to guide a multibody dynamics simulation or improve the model-setup by performing parameter identification.

projects:

Term: 2016-12-01 - 2020-06-30
Funding source: BMBF / Verbundprojekt
Project leader: Sigrid Leyendecker

Das Verbundprojekt DYMARA hat die Entwicklung eines innovativen digitalen Menschmodells (Manikins) mit  detaillierter Modellierung der Skelettmuskulatur und schnellen numerischen Algorithmen zum Ziel. Mit diesem Manikin soll es möglich werden, den Menschen simulationsgestützt auf optimale Weise in sein Arbeitsumfeld zu integrieren und Ermüdungen, Erkrankungen sowie Unfälle am Arbeitsplatz zu vermeiden. Neben diesen ergonomischen Gesichtspunkten soll das Menschmodell auch zur Therapieplanung im m…

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Term: since 2017-09-01
Project leader: Sigrid Leyendecker

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Term: 2015-11-01 - 2018-03-31
Funding source: Industrie
Project leader: Sigrid Leyendecker

The goal of this project is to apply techniques of biomechanics and optimal control to generate realistic human-like motions of the DHM from generic working instructions like for example move a box from A to B. Such a model would enable the engineers to take into account physical workloads and reachability issues in virtual assembly planning.

The digital human is modeled as a biomechanical multibody system with muscles as actuators. The motions of the DHM for specific working…

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Term: 2021-07-01 - 2025-06-30
Funding source: DFG / Sonderforschungsbereich (SFB)
Project leader: Sigrid Leyendecker

The focus of the work programme is on the best possible integration of
empathokinesthetic sensor data into biomechanical models. Specifically,
degenerative movement restrictions of the hand are recorded by EmpkinS
and reference sensor technology and the data are optimally integrated
into the mathematical formulation of the optimal control problem
depending on data type, measurement frequency and fuzziness, etc. The
aim of the project is to develop a model of the degenerative hand
movement. Objective biomarkers of healthy or impaired movement function
are identified through movement tracking and prediction.

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Term: 2020-10-01 - 2023-09-30
Funding source: DFG-Einzelförderung / Sachbeihilfe (EIN-SBH)
Project leader: Sigrid Leyendecker

People with joint disorders or lower limb loss require a technical substitute that restores biomechanical function and body integrity. Prothetic structures not only need to fulfil their respective functional requirements (allowing a save and wide range of motion at low energy expenditure and without impairing the person's body) but also the appearance of the resulting motion (including aesthetic properties like natural and symmetric gait patterns) is of high relevance. Since measurement of in vivo…

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Term: 2020-01-01 - 2020-12-31
Funding source: Fraunhofer-Gesellschaft
Project leader: Sigrid Leyendecker

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involved scientists:

  • Sigrid Leyendecker
  • Johann Penner
  • Simon Heinrich
  • Eduard Scheiterer
  • Uday Phutane
  • Toufik Bentaleb
  • Michael Klebl

publications:

For a list of publications related to motion capturing, please look here.

 

Institute of Applied Dynamics
Friedrich-Alexander-Universität Erlangen-Nürnberg

Immerwahrstrasse 1
91058 Erlangen
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