Uncertainty propagation in multibody human model dynamics

Antoine Muller 1, 2 Charles Pontonnier 2, 3, 1 Georges Dumont 2, 1
1 MIMETIC - Analysis-Synthesis Approach for Virtual Human Simulation
UR2 - Université de Rennes 2, Inria Rennes – Bretagne Atlantique , IRISA_D6 - MEDIA ET INTERACTIONS
Abstract : In biomechanics, calibration of body segment inertial parameters (BSIP) is crucial to take into account subject morphological specificities. To avoid strenuous protocols, identification methods based on rigid body dynamics laws have been proposed. Thanks to a motion capture system and force platforms, these methods optimize BSIP by minimizing errors in the equations of motion. These errors can be defined as the dynamic resid-uals reflecting inaccuracies arising from estimated BSIP, as well as from kinematics and force plate measurements. The current study aims at evaluating the part of uncertainty on the dynamic residuals directly related to kinematics and force plate measurements. To answer this question, we captured the movements of 10 participants performing a standardized motion. We then applied a Monte Carlo-based approach to introduce variations in the kinematics and force plate measurements, and evaluated the reconstructed difference on the dynamic residuals. Results show that, first, the BSIP evaluation using a regression method seemed to be an acceptable estimate for the studied subjects. Second, the part of uncertainty in the dynamic residuals was significantly higher than the dynamic resid-uals obtained. In conclusion, a subject-specific calibration of the BSIP based on dynamic residuals, for this model and protocol, seems irrelevant and prone to overfitting of BSIP.
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Article dans une revue
Multibody System Dynamics, Springer Verlag, 2017
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Soumis le : mercredi 8 février 2017 - 17:03:49
Dernière modification le : jeudi 15 novembre 2018 - 11:59:01


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  • HAL Id : hal-01462185, version 1


Antoine Muller, Charles Pontonnier, Georges Dumont. Uncertainty propagation in multibody human model dynamics. Multibody System Dynamics, Springer Verlag, 2017. 〈hal-01462185〉



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