Uncertainty propagation in multibody human model dynamics

被引:15
|
作者
Muller, Antoine [1 ]
Pontonnier, Charles [2 ]
Dumont, Georges [1 ]
机构
[1] IRISA, Ecole Normale Super Rennes, INRIA MimeTIC, Campus Beaulieu, F-35042 Rennes, France
[2] IRISA, Ecole Normale Super Rennes, INRIA MimeTIC, Ecoles St Cyr Coetquidan, Campus Beaulieu, F-35042 Rennes, France
关键词
Inverse dynamics; Kinematics; Dynamic residuals; Optimization; BSIP; Monte Carlo method; BODY SEGMENT PARAMETERS; HUMAN JOINT MOTION; ISB RECOMMENDATION; OPTIMIZATION; DEFINITIONS; SHOULDER; SYSTEMS;
D O I
10.1007/s11044-017-9566-7
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
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 residuals 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 residuals 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.
引用
收藏
页码:177 / 192
页数:16
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