Machine Learning for Personalisation of Biomechanical Movement Simulations (C01)


Acronym: SFB 1483 EmpkinS C01
Project leader:
Project members: , ,
Start date: 1. July 2021
End date: 30. June 2025
Funding source: DFG / Sonderforschungsbereich (SFB)

 

Abstract

The extent to which a neural network can be used to effectively personalise gait simulations using motion data is explored. We first investigate the influence of body parameters on gait simulation. An initial version of the personalisation is trained with simulated motion data, since ground truth data is known for this purpose. We then explore gradient-free methods to fit the network for experimental motion data. The resulting network is validated with magnetic resonance imaging, electromyography and intra-body variables.

Students

Open Theses / Student Projects

ID 2340: Approximate Inverse Optimal Control via Annealing and Warmstarts

https://www.mad.tf.fau.de/2023/03/23/id-2320/

Current Students

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Publications