A generic musculoskeletal model of the juvenile lower limb for biomechanical analyses of gait

Hainisch, Reinhard; Kranzl, Andreas; Lin, Yi-Chung; Pandy, Marcus G.; Gfoehler, Margit

doi:10.1080/10255842.2020.1817405

Cited by 13 publications

(14 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, marker-based scaling of a generic MSK models assumes that skeletal anatomy scales linearly between individuals. While this is accepted for adults, its suitability is still unclear for juvenile individuals [43]. Therefore, the adoption of a scaled ankle axis could explain the significant differences observed for the SGJ.…”

Section: Discussionmentioning

confidence: 99%

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

et al. 2021

View full text Add to dashboard Cite

No consensus exists on how to model human articulations within MSK models for the analysis of gait dynamics. We propose a method to evaluate joint models and we apply it to three models with different levels of personalization. The method evaluates the joint model’s adherence to the MSK hypothesis of negligible joint work by quantifying ligament and cartilage deformations resulting from joint motion; to be anatomically consistent, these deformations should be minimum. The contrary would require considerable external work to move the joint, violating a strong working hypothesis and raising concerns about the credibility of the MSK outputs. Gait analysis and medical resonance imaging (MRI) from ten participants were combined to build lower limb subject-specific MSK models. MRI-reconstructed anatomy enabled three levels of personalization using different ankle joint models, in which motion corresponded to different ligament elongation and cartilage co-penetration. To estimate the impact of anatomical inconsistency in MSK outputs, joint internal forces resulting from tissue deformations were computed for each joint model and MSK simulations were performed ignoring or considering their contribution. The three models differed considerably for maximum ligament elongation and cartilage co-penetration (between 5.94 and 50.69% and between −0.53 and −5.36 mm, respectively). However, the model dynamic output from the gait simulations were similar. When accounting for the internal forces associated with tissue deformation, outputs changed considerably, the higher the personalization level the smaller the changes. Anatomical consistency provides a solid method to compare different joint models. Results suggest that consistency grows with personalization, which should be tailored according to the research question. A high level of anatomical consistency is recommended when individual specificity and the behavior of articular structures is under investigation.

show abstract

Section: Discussionmentioning

confidence: 99%

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Thus, the main objective of this study was to identify the differences between direct kinematics Plugin-Gait vs inverse kinematics AnyBody models. It should be mentioned that only several works compare the kinematic parameters of different models [35,[51][52][53], because modelbased gait analysis or model validation on muscle function and related parameters are usually performed by inverse dynamics [40][41][42][65][66][67][68]. Furthermore, we did not find a comparison of the kinematic parameters obtained by the DK PiG and the IK AnyBody models used in our study.…”

Section: Plos Onementioning

confidence: 94%

Comparison of kinematic parameters of children gait obtained by inverse and direct models

et al. 2022

View full text Add to dashboard Cite

The purpose of this study is to compare differences between kinematic parameters of pediatric gait obtained by direct kinematics (DK) (Plug-in-Gait) and inverse kinematics (IK) (AnyBody) models. Seventeen healthy children participated in this study. Both lower extremities were examined using a Vicon 8-camera motion capture system and a force plate. Angles of the hip, knee, and ankle joints were obtained based on DK and IK models, and ranges of motion (ROMs) were identified from them. The standard error of measurement, root-mean-squared error, correlation r, and magnitude-phase (MP) metrics were calculated to compare differences between the models’ outcomes. The determined standard error of measurement between ROMs from the DK and IK models ranged from 0.34° to 0.58°. A significant difference was found in the ROMs with the exception of the left hip’s internal/external rotation. The mean RMSE of all joints’ amplitudes exceeded the clinical significance limit and was 13.6 ± 4.0°. The best curve angles matching nature were found in the sagittal plane, where r was 0.79 to 0.83 and MP metrics were 0.05 to 0.30. The kinematic parameters of pediatric gait obtained by IK and DK differ significantly. Preferably, all of the results obtained by DK must be validated/verified by IK, in order to achieve a more accurate functional assessment of the individual. Furthermore, the use of IK expands the capabilities of gait analysis and allows for kinetic characterisation.

show abstract

“…For analysis, the model must match the subject for whom the input data are known in terms of mass, limb parameters (e.g. distances between joint centres and segment moments of inertia) and virtual marker positions [69,70]. Marker position optimization and scaling are intertwined processes because marker positions can, in part, determine segment dimensions.…”

Section: The Simulation 231 Scaling and Marker Optimizationmentioning

confidence: 99%

A review of musculoskeletal modelling of human locomotion

2021

View full text Add to dashboard Cite

Locomotion through the environment is important because movement provides access to key resources, including food, shelter and mates. Central to many locomotion-focused questions is the need to understand internal forces, particularly muscle forces and joint reactions. Musculoskeletal modelling, which typically harnesses the power of inverse dynamics, unites experimental data that are collected on living subjects with virtual models of their morphology. The inputs required for producing good musculoskeletal models include body geometry, muscle parameters, motion variables and ground reaction forces. This methodological approach is critically informed by both biological anthropology, with its focus on variation in human form and function, and mechanical engineering, with a focus on the application of Newtonian mechanics to current problems. Here, we demonstrate the application of a musculoskeletal modelling approach to human walking using the data of a single male subject. Furthermore, we discuss the decisions required to build the model, including how to customize the musculoskeletal model, and suggest cautions that both biological anthropologists and engineers who are interested in this topic should consider.

show abstract

A generic musculoskeletal model of the juvenile lower limb for biomechanical analyses of gait

Cited by 13 publications

References 41 publications

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

Modeling Musculoskeletal Dynamics during Gait: Evaluating the Best Personalization Strategy through Model Anatomical Consistency

Comparison of kinematic parameters of children gait obtained by inverse and direct models

A review of musculoskeletal modelling of human locomotion

Contact Info

Product

Resources

About