Adjustments to McConville et al. and Young et al. body segment inertial parameters

Dumas, Raphaël; Chèze, Laurence; Verriest, Jean-Pierre

doi:10.1016/j.jbiomech.2006.02.013

Cited by 454 publications

(358 citation statements)

References 49 publications

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“…This might be attributed to the fact that the volunteers were regular people (healthy, no high-level athletes, neither underweight nor obese: Body Mass Index within [18.5 30] range). So we can suppose that, for these subjects, the anthropometric data of [5] were close to the subject-specific parameters.…”

Section: Comparison With the Reference Dynamic Residualsmentioning

confidence: 73%

“…Dynamic residuals computation Equation (4) can be developed as a floatingbase dynamics equation (5). The upper part of the equation describes the 6 DoF motion of the base (e.g.…”

Section: Inverse Dynamicsmentioning

confidence: 99%

“…Using a set of postures, limb lengths and model marker positions were optimized to best fit captured marker positions. From this calibrated model, BSIP were then estimated using the regression method proposed by [5]. This regression method, widely used in human multibody dynamics analyses, is the one evaluated with respect to hypothesis H1.…”

Section: Experimental Protocol and Biomechanical Modelmentioning

confidence: 99%

“…First, regression methods based on anthropometric databases collected from cadaver studies [3,4] or from in vivo body scanning [5,6,7,8] have been proposed to estimate BSIP. These methods aim at scaling BSIP based on subject's height and weight.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty propagation in multibody human model dynamics

2017

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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.

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Section: Comparison With the Reference Dynamic Residualsmentioning

confidence: 73%

“…Dynamic residuals computation Equation (4) can be developed as a floatingbase dynamics equation (5). The upper part of the equation describes the 6 DoF motion of the base (e.g.…”

Section: Inverse Dynamicsmentioning

confidence: 99%

Section: Experimental Protocol and Biomechanical Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Uncertainty propagation in multibody human model dynamics

2017

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“…Finally, a fitted spline function on the marker trajectories is differentiated to obtain the velocities and accelerations of the points. To carry out dynamics calculations, all the required inertial properties and segment dimensions are selected based on the existing anthropometric data [10] with some adjustments (Table 1). The moment of inertias are expressed in the local axes.…”

Section: Motion Capture and Data Analysismentioning

confidence: 99%

Effects of foot modelling on the human ankle kinematics and dynamics

Gholami

Vilà

Kövecses

et al. 2015

Mechanism and Machine Theory

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In this study, effects of some of the foot modelling assumptions on the ankle kinematics and dynamics are investigated based on the experimental data. For the kinematics analysis, the appropriateness of the stationary axis of rotation of the human ankle flexion is examined. Moreover, an interpolated function which is capable of predicting the directional changes of this axis is proposed. For the dynamics analysis, two main modelling assumptions of the number of the foot segments and the dimension of the foot model are the subject of the study. To this end, the ankle joint torque and power are selected as the comparison indicators and inverse dynamics analyses are carried out. The analyses show that the number of segments of the foot model does not have a considerable effect on the calculated ankle joint torque. On the other hand, the calculated ankle power is highly affected by both of the segmentation and the dimension of the foot model.

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The ideal couch tracking system—Requirements and evaluation of current systems

Jöhl

Ehrbar

Gückenberger

et al. 2019

J Applied Clin Med Phys

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Introduction: Intrafractional motion can cause substantial uncertainty in precision radiotherapy. Traditionally, the target volume is defined to be sufficiently large to cover the tumor in every position. With the robotic treatment couch, a real-time motion compensation can improve tumor coverage and organ at risk sparing. However, this approach poses additional requirements, which are systematically developed and which allow the ideal robotic couch to be specified.Methods and materials: Data of intrafractional tumor motion were collected and analyzed regarding motion range, frequency, speed, and acceleration. Using this data, ideal couch requirements were formulated. The four robotic couches Protura, Perfect Pitch, RoboCouch, and RPSbase were tested with respect to these requirements. Results:The data collected resulted in maximum speed requirements of 60 mm/s in all directions and maximum accelerations of 80 mm/s 2 in the longitudinal, 60 mm/s 2 in the lateral, and 30 mm/s 2 in the vertical direction. While the two robotic couches RoboCouch and RPSbase completely met the requirements, even these two showed a substantial residual motion (40% of input amplitude), arguably due to their time delays. Conclusion:The requirements for the motion compensation by an ideal couch are formulated and found to be feasible for currently available robotic couches. However, the performance these couches can be improved further regarding the position control if the demanded speed and acceleration are taken into account as well. K E Y W O R D Sintrafractional motion, motion compensation, treatment couch tracking, robotic couch

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Adjustments to McConville et al. and Young et al. body segment inertial parameters

Cited by 454 publications

References 49 publications

Uncertainty propagation in multibody human model dynamics

Uncertainty propagation in multibody human model dynamics

Effects of foot modelling on the human ankle kinematics and dynamics

The ideal couch tracking system—Requirements and evaluation of current systems

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