Dynamic identification of human trunk behavior as a diagnosis tool for pathologic problems

Moalla, Ferdaous; Mehrez, Sadok; Najar, Fehmi

doi:10.1109/mecbme.2018.8402405

Cited by 3 publications

(2 citation statements)

References 20 publications

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“…The trunk biomechanical model is a lumped type numerical model that enables calculation of the nonlinear static response of the torso, to an input set of applied loads, at a given posture of the body. The model (Figure 2) includes the spine, the rib cage, and 174 muscles [21,22]. The vertebrae, the intervertebral discs, the sternum, and the ribs are represented by beam elements and the ligaments are modeled as linear springs.…”

Section: Trunk Numerical Modelmentioning

confidence: 99%

Numerical Identification of Deep Muscle Residual Tensions (Tones) Based on Multi-Directional Trunk Stiffness Data

2022

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This work proposes an identification methodology to estimate the residual tension values (tones) for the human trunk muscles, including the deep ones, using multidirectional trunk stiffness data in association with numerical modeling. The role of this residual muscle tension or contraction is to maintain posture and balance. Knowledge of the tone is useful for the diagnosis and treatment of several spinal diseases and is important for realistic modeling and numerical simulation of trunk behavior. Most of the existing techniques for the measurement and estimation of muscle tones, such as electromyography, are restricted to superficial muscles. Those designed for deep muscles are invasive and present risks of infection and pain. In contrast, the proposed identification approach is painless and safe for the subject. It proceeds by matching the experimental trunk stiffness with numerical upper and lower estimates of the stiffness, to construct an inclusive solution domain of possible tone values of superficial as well as deep trunk muscles. By dividing the trunk muscles into three classes, each assumed to share the same tone ratio, a reasonable solution domain is obtained that exhibits a significant overlap with ranges of muscle tones found in the literature.

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Section: Trunk Numerical Modelmentioning

confidence: 99%

Numerical Identification of Deep Muscle Residual Tensions (Tones) Based on Multi-Directional Trunk Stiffness Data

2022

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“…Others are associated with the data interpretation and processing and depend on the adopted hypotheses and the models used to calculate the experimental stiffness [ 9 – 13 ]. In addition to experiments, numerical models of the trunk have been developed for the analysis and simulation of the trunk behavior [ 3 , 14 , 15 ]. Models that capture the details of this behavior may be useful for the interpretation and explanation of test results [ 8 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Directional Dependence of Experimental Trunk Stiffness: Role of Muscle-Stiffness Variation of Nonneural Origin

Mehrez

Smaoui

2020

Applied Bionics and Biomechanics

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Trunk stiffness is an important parameter for trunk stability analysis and needs to be evaluated accurately. Discrepancies regarding the dependence of trunk stiffness on the direction of movement in the sagittal plane suggest inherent sources of error that require explanation. In contrast to the common assumption that the muscle stiffness remains constant prior to the induction of a reflex during position perturbations, it is postulated that muscle-stiffness changes of nonneural origin occur and alter the experimental trunk stiffness, causing it to depend on the sagittal direction. This is confirmed through reinterpretation of existing test data for a healthy subject, numerical simulation, and sensitivity analysis using a biomechanical model. The trunk stiffness is determined through a static approach (in forward and backward directions) and compared with the model stiffness for assumed scenarios involving deactivated muscles. The difference in stiffness between the opposite directions reaches 17.5% without a preload and decreases when a moderate vertical preload is applied. The increased muscle activation induced by preloads or electrical stimuli explains the apparent discrepancies observed in previous studies. The experimental stiffness invariably remains between low and high model-stiffness estimates based on extreme scenarios of the postulated losses of muscle activation, thereby confirming our hypothesis.

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Multi-body musculoskeletal dynamic model of the human trunk based on an experimental approach

2022

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Dynamic identification of human trunk behavior as a diagnosis tool for pathologic problems

Cited by 3 publications

References 20 publications

Numerical Identification of Deep Muscle Residual Tensions (Tones) Based on Multi-Directional Trunk Stiffness Data

Numerical Identification of Deep Muscle Residual Tensions (Tones) Based on Multi-Directional Trunk Stiffness Data

Directional Dependence of Experimental Trunk Stiffness: Role of Muscle-Stiffness Variation of Nonneural Origin

Multi-body musculoskeletal dynamic model of the human trunk based on an experimental approach

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