A generic detailed rigid-body lumbar spine model

Zee, Mark de; Hansen, Lars; Wong, Christian; Rasmussen, John; Simonsen, Erik B.

doi:10.1016/j.jbiomech.2006.05.030

Cited by 266 publications

(195 citation statements)

References 31 publications

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“…1) was obtained the validity of its usage for the purpose of this study against the previous studies [9,10]. In brief, the musculoskeletal model consists of several body components: the skull, arms, legs, pelvis, and spine which are rigid bodies and connected with rigid joints.…”

Section: The Model Descriptionmentioning

confidence: 81%

“…In brief, the musculoskeletal model consists of several body components: the skull, arms, legs, pelvis, and spine which are rigid bodies and connected with rigid joints. The masses and inertia properties of each body segment were applied based on the previous experimental studies [9,11]. The spine region consists of the cervical, thoracic and lumbar spines as well as the sacrum and the cervical and thoracic spines are modeled as a single lumped segment while the lumbar spine consists of five rigid bodies.…”

Section: The Model Descriptionmentioning

confidence: 99%

“…2). All muscles were represented as single force components which can exert only tensile forces [9,10]. The muscle dynamics features such as force-length and force-velocity relationships were not considered and also no passive element properties, tendons in muscle were considered.…”

Section: The Model Descriptionmentioning

confidence: 99%

“…Also it is hard to distinguish the certain muscle among superficial and deep muscles in the overlaid musculature [7,8]. Therefore, alternative approach combining with analytical musculoskeletal models [9,10] has been widely used to predict internal joint forces and muscle forces. This computational modeling approach can be useful to explore the area where the experimental approaches are hardly applied to quantify the internal forces and provide the detailed muscle architecture including hundreds of muscle fascicles, ligaments, segments and joints and attained the validity of the model into biomechanical studies against a series of experimental data.…”

Section: Introductionmentioning

confidence: 99%

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3-D Inverse Dynamics Analysis of the Effect of Maximum Muscle Force Capacities on a Musculoskeletal System

Han¹

2014

Journal of Electrical Engineering and Technology

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-It is known that muscle strength of human body can alter or deteriorate as aging. In this study, we present an inverse dynamics simulation to investigate the effect of muscle strength on performing the daily activities. A 3D musculoskeletal model developed in this study includes several segments of whole body, long and short muscles, ligaments and disc stiffness. Five daily activities such as standing, flexion, finger tip to floor, standing lift close and lifting flexed were simulated with varying the maximum muscle force capacities (MFC) of each muscle fascicles from 30 to 90 N/cm 2 with an increment of 30 N/cm 2 . In the result, no solution can be obtained for finger tip to floor and lifting flexed with 30 N/cm 2 . Even though the solution was available for standing lift close activity in case of 30 N/cm² capacity, many of muscle fascicles hit the upper bound of muscle strength which means that it is not physiologically possible to perform the acvities in reality. For lifing flexed, even the case of 60 N/cm 2 capaciy, represents the moderate healthy people, was not able to find the solutions, showing that 18 muscles among 258 muscle fascicles reached 100% of muscle capacity. The estimated results imply that people who have low muscle strength such as elders or rehabilitation patients were required higher muscle work to perform and maintain the same daily activities than healthy one.

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Section: The Model Descriptionmentioning

confidence: 81%

Section: The Model Descriptionmentioning

confidence: 99%

Section: The Model Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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3-D Inverse Dynamics Analysis of the Effect of Maximum Muscle Force Capacities on a Musculoskeletal System

Han¹

2014

Journal of Electrical Engineering and Technology

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“…Complementary studies could be explored: a first approach could consist in adaptively modifying the kinematical model depending on the most important reconstruction error. This could for instance take into account the complex closed-loop geometry of the shoulder [36] or a detailed lumbar spine model [37]. A second approach could be to select only a set of motion sequences to perform BSIP calibration, by selecting only sequences where the uncertainties introduced by the reconstruction error would be sufficiently low to achieve a subject-specific BSIP calibration.…”

Section: Comparison With the Reference Dynamic Residualsmentioning

confidence: 99%

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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A synergy‐based control solution for overactuated characters: Application to throwing

Ruiz

Pontonnier

Levy

et al. 2016

Computer Animation & Virtual

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In the current paper, we present a bio-inspired solution for the control of overactuated models in animation, such as musculoskeletal models. This solution consists in the extraction of muscle synergies from human experiments, followed by a control method consisting of a series of optimizations to adapt muscle parameters and synergies to match experimental data. We apply the framework on throwing motions and the results show that these motions can be accurately reproduced on a character with a simplified muscular structure, while preserving important characteristics in the original synergies or control signals.2

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A generic detailed rigid-body lumbar spine model

Cited by 266 publications

References 31 publications

3-D Inverse Dynamics Analysis of the Effect of Maximum Muscle Force Capacities on a Musculoskeletal System

3-D Inverse Dynamics Analysis of the Effect of Maximum Muscle Force Capacities on a Musculoskeletal System

Uncertainty propagation in multibody human model dynamics

A synergy‐based control solution for overactuated characters: Application to throwing

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