Computer models that estimate the force generation capacity of lower limb muscles have become widely used to simulate the effects of musculoskeletal surgeries and create dynamic simulations of movement. Previous lower limb models are based on severely limited data describing limb muscle architecture (i.e., muscle fiber lengths, pennation angles, and physiological cross-sectional areas). Here, we describe a new model of the lower limb based on data that quantifies the muscle architecture of 21 cadavers. The model includes geometric representations of the bones, kinematic descriptions of the joints, and Hill-type models of 44 muscle–tendon compartments. The model allows calculation of muscle–tendon lengths and moment arms over a wide range of body positions. The model also allows detailed examination of the force and moment generation capacities of muscles about the ankle, knee, and hip and is freely available at www.simtk.org.

/pdf/a-model-of-the-lower-limb-for-analysis-of-human-movement-1nu8hu189y.pdf

A Model of the Lower Limb for Analysis of Human Movement

Objective: Musculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait. Methods: Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running. Results: Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data. Conclusion: These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity. Significance: The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/ , allowing others to reproduce these results and create their own simulations.

Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait

Computational modeling and simulation of neuromusculoskeletal (NMS) systems enables researchers and clinicians to study the complex dynamics underlying human and animal movement. NMS models use equations derived from physical laws and biology to help solve challenging real-world problems, from designing prosthetics that maximize running speed to developing exoskeletal devices that enable walking after a stroke. NMS modeling and simulation has proliferated in the biomechanics research community over the past 25 years, but the lack of verification and validation standards remains a major barrier to wider adoption and impact. The goal of this paper is to establish practical guidelines for verification and validation of NMS models and simulations that researchers, clinicians, reviewers, and others can adopt to evaluate the accuracy and credibility of modeling studies. In particular, we review a general process for verification and validation applied to NMS models and simulations, including careful formulation of a research question and methods, traditional verification and validation steps, and documentation and sharing of results for use and testing by other researchers. Modeling the NMS system and simulating its motion involves methods to represent neural control, musculoskeletal geometry, muscle-tendon dynamics, contact forces, and multibody dynamics. For each of these components, we review modeling choices and software verification guidelines; discuss variability, errors, uncertainty, and sensitivity relationships; and provide recommendations for verification and validation by comparing experimental data and testing robustness. We present a series of case studies to illustrate key principles. In closing, we discuss challenges the community must overcome to ensure that modeling and simulation are successfully used to solve the broad spectrum of problems that limit human mobility.

Is My Model Good Enough? Best Practices for Verification and Validation of Musculoskeletal Models and Simulations of Movement

Shoulder function: the perfect compromise between mobility and stability.

外反母趾の Biomechanical analysis-靴のヒール高との関連

Morphological muscle and joint parameters for musculoskeletal modelling of the lower extremity

Background:
To assist in the treatment of gait disorders, an inverse and forward 3D musculoskeletal model of the lower extremity will be useful that allows to evaluate if–then scenarios. Currently available anatomical datasets do not comprise sufficiently accurate and complete information to construct such a model. The aim of this paper is to present a complete and consistent anatomical dataset, containing the orientations of joints (hip, knee, ankle and subtalar joints), muscle parameters (optimum length, physiological cross sectional area), and geometrical parameters (attachment sites, ‘via’ points).

Methods:
One lower extremity, taken from a male embalmed specimen, was studied. Position and geometry were measured with a 3D-digitizer. Optotrak was used for measurement of rotation axes of joints. Sarcomere length was measured by laser diffraction.

Findings:
A total of 38 muscles were measured. Each muscle was divided in different muscle lines of action based on muscle morphology. 14 Ligaments of the hip, knee and ankle were included.

Interpretation:
The presented anatomical dataset embraces all necessary data for state of the art musculoskeletal modelling of the lower extremity. Implementation of these data into an (existing) model is likely to significantly improve the estimation of muscle forces and will thus make the use of the model as a clinical tool more feasible.

Morphological Muscle and joint parameters for musculoskeletal modelling of the lower extremity

https://repository.tudelft.nl/islandora/object/uuid%3Aa1e9d161-7c6e-4452-b68b-291f08117c55/datastream/OBJ/download

Power in sports: A literature review on the application, assumptions, and terminology of mechanical power in sport research.

In the current project, we aim to provide speed skaters with real-time feedback on how to improve their skating performance within an individual stroke. The elite skaters and their coaches wish for a system that determines the mechanical power per stroke. The push-off force of the skater is a crucial variable in this power determination. In this study, we present the construction and calibration of a pair of wireless instrumented klapskates that can continuously and synchronously measure this push-off force in both the lateral direction and normal direction of the skate and the centre of pressure of these forces. The skate consists of a newly designed rigid bridge (0.6 kg), embedding two three-dimensional force sensors (Kistler 9602, Kistler Group, Winterthur, Switzerland), which fits between most individual skate shoes and Maple skate blades. The instrumented klapskates were calibrated on a tensile testing machine, where they proved to be unaffected to temperature conditions and accurate up to an RMS of 42 N (SEM = 1 N) in normal and up to an RMS of 27 N (SEM = 1 N) in lateral direction. Furthermore, the centre of pressure of these forces on the blade was determined up to a mean error of 10.1 mm (SD = 6.9 mm). On-ice measurements showed the possibility of recording with both skates simultaneously and synchronously, straights as well as curves. The option to send data wirelessly and real-time to other devices makes it possible to eventually provide skaters and coaches with visual real-time feedback during practice.

/pdf/wireless-instrumented-klapskates-for-long-track-speed-5gqk0wzgyw.pdf

F.C.T. van der Helm

Papers

Morphological muscle and joint parameters for musculoskeletal modelling of the lower extremity

Morphological Muscle and joint parameters for musculoskeletal modelling of the lower extremity

Power in sports: A literature review on the application, assumptions, and terminology of mechanical power in sport research.

Wireless instrumented klapskates for long-track speed skating

Getting in shape: Reconstructing three-dimensional long-track speed skating kinematics by comparing several body pose reconstruction techniques.