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49 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3>
OpenSim
- OpenSim is a freely available, user extensible software system that lets users develop models of musculoskeletal structures and create dynamic simulations of movement.
Find out how to join the community and see the work being performed using OpenSim at <a href="http://opensim.stanford.edu">opensim.stanford.edu</a>.
Access all of our OpenSim resources at the new <br /><a href="http://opensim.stanford.edu/support/index.html"><b style="color:#900; font-size:16px;">Support Site</b></a>.
Watch our <a href="http://www.youtube.com/watch?v=ME0VHfCtIM0">Introductory Video</a> get an overview of the OpenSim project and see how modeling can be used to help plan surgery for children with cerebral palsy.
<iframe width="560" height="315" src="https://www.youtube.com/embed/ME0VHfCtIM0" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> | |
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Registered: 2006-03-23 18:48 |
OpenMM
- OpenMM is a toolkit for molecular simulation. It can be used either as a stand-alone application for running simulations, or as a library you call from your own code. It
provides a combination of extreme flexibility (through custom forces and integrators), openness, and high performance (especially on recent GPUs) that make it truly unique among simulation codes.
<b>NEED HELP?</b> Check out the discussion forums under <a href="https://simtk.org/forums/viewforum.php?f=161">Public Forums</a> and the material from our workshops under <a href="https://simtk.org/project/xml/downloads.xml?group_id=161">Downloads</a>.
<b>GET STARTED QUICKLY:</b> Tutorials and sample scripts to run OpenMM are available in the <a href="http://wiki.simtk.org/openmm/VirtualRepository">OpenMM Code Repository</a>.
<b>SOURCE CODE:</b> The source code for OpenMM is available under <a href="https://simtk.org/project/xml/downloads.xml?group_id=161">Downloads</a> and also from the <a href="http://www.github.com/SimTk/openmm">Github Source Code Repository</a>.
<b>BENCHMARKS:</b> A collection of <a href="http://wiki.simtk.org/openmm/Benchmarks">benchmarks</a> is available to show the performance of OpenMM simulating a variety of molecular systems.
<b>CITING OPENMM:</b> Any work that uses OpenMM should cite the papers listed on the <a href="https://simtk.org/project/xml/publications.xml/?group_id=161">Publications</a> page. | |
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Registered: 2006-11-16 18:27 |
SimVascular: Cardiovascular Modeling and Simulation
- SimVascular is an open source software suite for cardiovascular simulation, providing a complete pipeline from medical image data to 3D model construction, meshing, and blood flow simulation. SimVacular represents the state of the art in cardiovascular simulation, including advanced tools for physiologic boundary conditions, fluid structure interaction, and an accurate and efficient finite element Navier-Stokes solver. SimVascular integrates custom code with best-in-class open source packages to support clinical and basic science research.
DOCUMENTATION and CLINICAL EXAMPLES are available on the main project website at:
http://www.simvascular.org
Demo projects and examples for SimVascular can be downloaded at:
https://simtk.org/projects/sv_tests
Interested users should join the mailing list for the SimVascular project on simtk.org to be notified about upcoming releases and workshop announcements.
<b>If you use SimVascular for your work, please cite the following publication:</b>
Updegrove, A., Wilson, N., Merkow, J., Lan, H., Marsden, A. L. and Shadden, S. C., <a href="http://link.springer.com/article/10.1007/s10439-016-1762-8">SimVascular - An open source pipeline for cardiovascular simulation</a>, <em>Annals of Biomedical Engineering</em> (2016). DOI:10.1007/s10439-016-1762-8
The SimVascular project is funded by the NSF SSI program under Program Officers Rajiv Ramnath (ACI) and Sumanta Acharya (CBET). | |
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Registered: 2007-03-13 21:42 |
Practical Annotation and Exchange of Virtual Anatomy
- Representation of anatomy in a virtual form is at the heart of clinical decision making, biomedical research, and medical training. Virtual anatomy is not limited to description of geometry but also requires appropriate and efficient labeling of regions - to define spatial relationships and interactions between anatomical objects; effective strategies for pointwise operations - to define local properties, biological or otherwise; and support for diverse data formats and standards - to facilitate exchange between clinicians, scientists, engineers, and the general public. Development of aeva, a free and open source software package (library, user interfaces, extensions) capable of automated and interactive operations for virtual anatomy annotation and exchange, is in response to these currently unmet requirements. This site serves for aeva outreach, including dissemination the software and use cases. The use cases drive design and testing of aeva features and demonstrate various workflows that rely on virtual anatomy.
aeva downloads:
Downloads (https://simtk.org/frs/?group_id=1767)
Kitware data repository (https://data.kitware.com/#folder/5e7a4690af2e2eed356a17f2)
aeva documentation:
Guides and tutorials (https://aeva.readthedocs.io)
aeva videos:
Short instructions (https://www.youtube.com/channel/UCubfUe40LXvBs86UyKci0Fw)
aeva source code:
Kitware source code repository (https://gitlab.kitware.com/aeva)
aeva forum:
Forums (https://simtk.org/plugins/phpBB/indexPhpbb.php?group_id=1767 ) | |
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Registered: 2019-08-28 01:27 |
Statistical analysis of conformational ensembles
- This project provides computational tools and methods to analyze conformational ensembles of biomolecules, as well as their assemblies, such as those obtained from molecular simulations.
(A) PROTEINS: The molecular understanding of the functional regulation of proteins requires assessment of various states, including active and inactive states, as well as their interdependencies. For several proteins, their various states can be distinguished from each other on the basis of their minimum energy 3D structures. For many other proteins, like GPCRs, PDZ domains, nuclear transcription factors, heat shock proteins, T-cell receptors and viral attachment proteins, their states can be distinguished categorically from each other only when their finite-temperature conformational ensembles are considered alongside their minimum-energy structures. We are developing tools/methods for:
(A1) Direct comparison of conformational ensembles - The traditional approach to compare two or more conformational ensembles is to compare their respective summary statistics. This approach is, however, prone to artifactual bias, as data is compared after dimensionality reduction. The proper way to compare ensembles is to compare them directly with each other and prior to any dimensionality reduction. g_ensemble_comp is a tool we have developed that does just that and reports the difference between ensembles in terms of a true metric defined by the zeroth law of thermodynamics.
(A2) Prediction of allosteric signaling networks - method under development.
(B) LIPID MEMBRANES: The surface area of a lipid bilayer is related fundamentally to many other observables, such as thermal phase transitions and domain formation in mixed lipid bilayers. We have developed g_tessellate_area to compute the 3D surface area of a bilayer using Delunay tessellation. | |
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Activity Percentile: 94.66 Registered: 2015-09-15 17:52 |
Predicting Cell Deformation from Body Level Mechanical Loads
- This project is a NIBIB/NIH funded study (1R01EB009643-01) to establish models and computational platforms to predict cellular deformations from joint level mechanical loading.
Collaborators:
Ahmet Erdemir (PI), Amit Vasanji, Jason Halloran (Cleveland Clinic)
Cees Oomens, Frank Baaijens (Eindhoven University of Technology)
Jeff Weiss (University of Utah)
Farshid Guilak (Duke University)
Summary (from grant proposal):
Cells of the musculoskeletal system are known to have a biological response to deformation. Deformations, when abnormal in magnitude, duration, and/or frequency content, can lead to cell damage and possible disruption in homeostasis of the extracellular matrix. These mechanisms can be studied in an isolated fashion but connecting mechanical cellular response to organ level mechanics and human movement requires a multiscale approach. At the organ level, physicians perform surgical procedures, investigators try to understand risk of injury, and clinicians prescribe preventive and therapeutic interventions. Many of these operations are aimed at management and prevention of cell damage, and to associate joint level mechanical markers of failure to cell level failure mechanisms. Through human movement, one explores neuromuscular control mechanisms and the influence of physical activity on musculoskeletal tissue properties. At a lower level, mechanical sensation of cell deformations regulate movement control. Physical rehabilitation and exercise regimens are prescribed to promote tissue healing and/or strengthening through cellular regeneration. The knowledge of the mechanical pathway, through which the body level loads are distributed between organs, then within the tissues and further along the extracellular matrix and the cells, is critical for the success of various interventions. However, this information is not established. The goal of this research proposal is to portray that prediction of cell deformations from loads acting on the human body, therefore a clear depiction of the mechanical pathway, is possible, if a multiscale simulation approach is used. Multiresolution models of the knee joint, representative of joint, tissue and cell structure and mechanics, will be developed for this purpose. The knee endures high rates of traumatic injury to its soft tissue structures and it is predominantly affected by osteoarthritis, chronically induced by abnormalities in mechanical loading or how it is transferred to the cartilage. Through multiscale mechanical coupling of these models, a map of cellular deformation in cartilage, ligaments and menisci under a variety of tibiofemoral joint loads will be obtained. Comprehensive mechanical testing at joint, tissue and cell levels will be conducted for parameter estimation and validation, including in vitro loading of the knee joint representative of lifelike loading scenarios. In addition, imaging modalities will capture joint and tissue anatomy, and spatial and deformation related information from cell and extracellular matrix. Advanced computational approaches will be used to obtain model properties and to facilitate multiscale simulations. The approach will combine the expertise of many investigators experienced in biomechanical modeling and experimentation at various biological scales, some with clinical expertise. In future, the research team will utilize this platform to establish the relationship between the structural and loading state of the knee and chondrocyte stresses to explore potential mechanisms of cartilage degeneration. Through documented dissemination of data and models, simulations of other pathologies and translation of the methodology to other organs can be carried out by any interested investigator. | |
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Registered: 2009-07-23 17:33 |
Specimen-Specific Models of the Healthy Knee
- As part of research funded by the National Institutes of Health, National Institute of Biomedical Imaging and Bioengineering (NIBIB), investigators at the University of Denver Center for Orthopaedic Biomechanics have made available a repository of experimental, image, and computational modeling data from mechanical testing of natural human knee biomechanics. It is uncommon for such a comprehensive dataset to be obtained. Therefore, we have made this repository available to assist the greater research community interested in the complexities and pathologies of knee health and mechanical function. Data are provided for 7 human knees (5 cadaveric subjects) and fall under two categories:
Image Data and Experimental & Computational Modeling Data.
Additional details about the data can be found at:
http://ritchieschool.du.edu/research/centers-institutes/orthopaedic-biomechanics/downloads/natural-knee-data/
This repository of natural knee data has been made available thanks to funding from the National Institutes of Health through National Institute of Biomedical Imaging and Bioengineering R01-EB015497. | |
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Registered: 2008-06-12 23:15 |
SCONE: Open Source Software for Predictive Simulation
- If SCONE is helpful for your research, please cite the following paper:
Geijtenbeek, T (2019). SCONE: Open Source Software for Predictive Simulation of Biological Motion. Journal of Open Source Software, 4(38), 1421, https://doi.org/10.21105/joss.01421 | |
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Registered: 2016-10-27 13:07 |
Lee-Son's Toolbox: a Toolbox that Converts VICON Mocap Data into OpenSim Inputs
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This toolbox converts VICON motion capture data into OpenSim inputs. Using this, you can easily and quickly obtain *.trc (marker trajectories) and *.mot (force plate data) files which can be used directly in OpenSim.
This toolbox automatically adapt to the number of markers, the name of markers, and the number of force plates that you used. Also, you can choose your VICON global coordinates.
This toolbox is free without warranty but we do ask for acknowledgement if used in publications. If you have any questions, please contact us by e-mail or public forums. | |
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Registered: 2011-08-30 02:08 |
Simulation of Constrained Musculoskeletal Systems in Task Space
- Objective: This work proposes an operational task space formalization of constrained musculoskeletal systems, motivated by its promising results in the field of robotics.
Methods: The change of representation requires different algorithms for solving the inverse and forward dynamics simulation in the task space domain. We propose an extension to the Direct Marker Control and an adaptation of the Computed Muscle Control algorithms for solving the inverse kinematics and muscle redundancy problems respectively.
Results: Experimental evaluation demonstrates that this framework is not only successful in dealing with the inverse dynamics problem, but also provides an intuitive way of studying and designing simulations, facilitating assessment prior to any experimental data collection.
Significance: The incorporation of constraints in the derivation unveils an important extension of this framework towards addressing systems that use absolute coordinates and topologies that contain closed kinematic chains. Task space projection reveals a more intuitive encoding of the motion planning problem, allows for better correspondence between observed and estimated variables, provides the means to effectively study the role of kinematic redundancy and, most importantly, offers an abstract point of view and control, which can be advantageous towards further integration with high level models of the precommand level.
Conclusion: Task-based approaches could be adopted in the design of simulation related to the study of constrained musculoskeletal systems.
The source code of the project can be found at: https://github.com/mitkof6/opensim-task-space.git
The new API of task space and constraint projection for OpenSim V4.0 is available at: https://github.com/mitkof6/task-space
<iframe width="560" height="315" src="https://www.youtube.com/embed/jfE14iWRZDs" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe> | |
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Registered: 2017-08-28 12:06 |
BlurLab -- 3D Microscopy Simulation Package
- BlurLab is an easy to use platform for generating simulated fluorescence microscopy data for use in mechanistic modeling visualization, image comparison, and hypothesis testing. The software accepts the 3D positions, intensities and labels of fluorescing objects that are produced by an underlying mechanistic model and transforms them into high quality simulated images. The program includes full 3D convolution with realistic (or even measured) point spread functions; inclusion of thermal, shot and custom noise spectra; simulations of mean and fully stochastic photobleacing; the ability to view scenes in wide-field and TIRF, and perform Z-slicing; and the ability to simulate FRAP experiments.
The software provides a platform for adjusting and saving these simulated images, as well as a number of helpful, semi-automated features to make image simulation easy and less error prone. | |
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Activity Percentile: 79.01 Registered: 2011-08-05 01:17 |
Calibrated EMG-Informed Neuromusculoskeletal Modelling Toolbox (CEINMS)
- The software permits the simulation of all the transformations that take place from the onset of muscle excitation to the generation of force in 34 musculotendon units and the resulting moments about six degrees of freedom (DOFs) in the lower extremity. The selected DOFs include: hip flexion-extension, hip adduction-abduction, hip internal-external rotation, knee flexion-extension, ankle plantar-dorsi flexion, and ankle subtalar angle.
Experimentally recorded electromyography (EMG) signals and three-dimensional joint angles can be used to determine the neural drive and the instantaneous kinematics for the multiple musculotendon units being modelled. Furthermore, the CEINMS software can estimate the excitation patterns for musculotendon units from which EMGs cannot be experimentally measured and adjust the EMG linear envelopes that may be subject to measurement errors and uncertainties, while ensuring dynamical consistency in the predicted joint moments.
Finally, the CEINMS software allows automatically identification of a number of parameters that determine the way musculotendon units activate and contract, which vary non-linearly across individuals. This is done via an optimization-based calibration procedure that adjusts the internal parameters to best reflect the anatomy and physiology of an individual. | |
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Activity Percentile: 75.95 Registered: 2013-02-19 05:59 |
OpenSim Moco
- OpenSim Moco is a software toolkit to solve optimal control problems with musculoskeletal models defined in OpenSim, including those with kinematic constraints. Using the direct collocation method, Moco can solve a wide range of problems, including motion tracking, motion prediction, and parameter optimization. The design of Moco focuses on ease-of-use, customizability, and extensibility. Just like OpenSim itself, Moco has interfaces in XML/command-line, Matlab, Python, Java, and C++.
<ul style="line-height: 100%;">
<li><a href="https://opensim.stanford.edu/moco">Read the <b>documentation</b></a></li>
<li><a href="https://github.com/opensim-org/opensim-moco">View the source code, report bugs, suggest features, or contribute on <b>GitHub</b></a></li>
<li><a href="https://www.biorxiv.org/content/10.1101/839381v1">Read the Moco preprint on <b>bioRxiv</b></a></li>
<li><a href="https://github.com/stanfordnmbl/mocopaper">Obtain the models, data, and code used to produce the Moco preprint</a></li>
<li><a href="https://opensim.stanford.edu/support/event_details.php?id=236&title=Webinar-OpenSim-Moco-Software-to-optimize-the-motion-and-control-of-OpenSim-models">Watch the recording of the Moco <b>webinar</b> from November, 2019</a></li>
</ul> | |
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Registered: 2019-11-03 22:27 |
Simbody: Multibody Physics API
- This project is a SimTK toolset providing general multibody dynamics capability, that is, the ability to solve Newton's 2nd law F=ma in any set of generalized coordinates subject to arbitrary constraints. (That's Isaac himself in the oval.) Simbody is provided as an open source, object-oriented C++ API and delivers high-performance, accuracy-controlled science/engineering-quality results.
Simbody uses an advanced Featherstone-style formulation of rigid body mechanics to provide results in Order(<em>n</em>) time for any set of <em>n</em> generalized coordinates. This can be used for internal coordinate modeling of molecules, or for coarse-grained models based on larger chunks. It is also useful for large-scale mechanical models, such as neuromuscular models of human gait, robotics, avatars, and animation. Simbody can also be used in real time interactive applications for biosimulation as well as for virtual worlds and games.
This toolset was developed originally by Michael Sherman at the Simbios Center at Stanford, with major contributions from Peter Eastman and others. Simbody descends directly from the public domain NIH Internal Variable Dynamics Module (IVM) facility for molecular dynamics developed and kindly provided by Charles Schwieters. IVM is in turn based on the spatial operator algebra of Rodriguez and Jain from NASA's Jet Propulsion Laboratory (JPL), and Simbody has adopted that formulation.
<b>SOURCE CODE:</b> Simbody is distributed in source form. The source code is maintained at <a href="https://www.github.com/simbody">GitHub</a>. You can get a zip of the latest stable release <a href="https://github.com/simbody/simbody/releases">here</a>, then build it on your Windows, Mac OSX, or Linux machine (you will need CMake and a compiler).
You can also clone the git repository and build the latest development version <a href="https://github.com/simbody/simbody">here</a>; the repository URL is https://github.com/simbody/simbody.git. If you would like to contribute bug fixes, new code, documentation, examples, etc. to Simbody (and we hope you will!), please fork the repository on GitHub and send pull requests.
If you are new to git, you may want to start with GitHub's <a href="https://help.github.com/categories/54/articles">Bootcamp tutorial</a>. | |
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Registered: 2005-07-26 19:52 |
Real-time OpenSim extension
- RTOSIM is a set of efficient and extensible C++ libraries to connect OpenSim with different devices. RTOSIM can use data provided by motion capture systems to solve OpenSim inverse kinematics and inverse dynamics on a frame-by-frame basis. Multiple threads operate concurrently to remove idle times due to communications with input and output devices, and the data flow is automatically managed by RTOSIM in order to preserve data integrity and avoid race conditions.
The inverse kinematics throughput is also enhanced by the use of multiple threads. From our tests, full-body inverse kinematics using the gait2392 can be solved up to 2000fps using 10+ cores.
RTOSIM source code is available on GitHub (see Downloads section). | |
Registered: 2016-05-24 07:56 |
Neuromusculoskeletal Modeling (NMSM) Pipeline
- <div style="display:inline-block"><a href="https://nmsm.rice.edu"><img src="https://nmsm.rice.edu/img/nmsm-pipeline-social-card.jpg" style="float:left;max-width:calc(100% - 40px);"></a></div>
Full project information is available at: https://nmsm.rice.edu. Please direct any inquiries about the NMSM Pipeline to us by posting your questions on this SimTK project forum or emailing nmsm@rice.edu.
Neuromusculoskeletal Modeling (NMSM) Pipeline is a set of tools for personalizing models and designing treatments for movement impairments and other pathologies.
The NMSM Pipeline consists of two toolsets:
Model Personalization - Personalize joint, muscle-tendon, neural control, and ground contact model properties.
Treatment Optimization - Design treatments using personalized models and an optimal control methodology.
At this time, Treatment Optimization requires the use of <a href="https://www.gpops2.com/">GPOPS-II optimal control solver</a>.
The NMSM Pipeline is written in MATLAB to lower the barrier for entry and to facilitate accessibility to the core codebase. We encourage users to modify the code to meet their needs.
The core codebase and examples are available to download for use in research. At this time, we ask that you wait to publish any work that uses the NMSM Pipeline until the journal article reference for the software is available. Please get in touch with us if you have any questions.
If you need help or want to start a discussion, please use the SimTK forum for this project.
Note: This project is a living entity. Updates will be made available as the Pipeline, examples, and tutorials are developed further and improved. | |
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Registered: 2022-07-07 14:55 |
Tim's OpenSim Utilities
- This project site is concerned with extending the functionality of OpenSim through the use of scripting tools and plugins.
Click on the downloads link to browse the set of freely available OpenSim tools for download.
*******************************************************
Previously delivered interactive webinars demonstrating
the use of the Pseudo-Inverse Induced Acceleration
plugin for OpenSim (IndAccPI).
http://www.stanford.edu/group/opensim/support/webinars.html
******************************************************* | |
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Registered: 2009-09-01 00:52 |
Efficient Methods for Multi-Domain Biomechanical Simulations
- This project is an NIH-funded collaboration between the Cleveland Clinic Foundation, the University of Utah, and the Stanford Center for Biomedical Computation (Simbios).
Grant number: 1 R01 EB006735-01
Principal Investigator: Ton van den Bogert
Co-Investigators: Ahmet Erdemir (CCF), Jeff Weiss (University of Utah), and Alan Freed (NASA Glenn Research Center)
Summary (from grant proposal):
In computational biomechanics, there are two well-developed but separate modeling domains: multibody dynamics for body movements, and finite element modeling for tissue deformations. Many clinical problems, however, span both domains. Whole body anatomy, mass distribution, and gait pattern are not typically represented in finite element models, yet these are important real-world factors that affect tissue stresses in the musculoskeletal system, which may contribute to clinical problems such as osteoarthritis and diabetic foot ulceration. Movement simulations, on the other hand, lack a representation of tissue deformations, which are indicators of mechanically induced pain and other sensory feedback (or the lack thereof) and will cause observable changes in gait. Exploration of these neuromusculoskeletal integrative mechanisms can only be accomplished by multi-domain simulations. Current techniques for multi-domain modeling are insufficient because forward dynamic movement simulations typically proceed along a sequence of many small steps in time. Finite element models are too slow to allow a solution at each of these steps. One may painstakingly produce a single movement simulation, but not the thousands of simulations that are required for predictive movement optimizations that are the state of the art in musculoskeletal dynamics. This has become a bottleneck for our own research, as well as for others. Our first aim, therefore, is to implement a generic, self-refining, surrogate modeling scheme, which aims to reproduce an underlying physics-based finite element model within a given error tolerance, but at a far lower computational cost. The self-refining feature is the key to reproduce the multi-dimensional input-output space of a typical finite element model of a joint or joint complex. Our second aim is to demonstrate the utility of these tools by connecting a finite element model of the foot to a complete musculoskeletal gait simulation, which will test the hypothesis that peak plantar pressures (an indicator of diabetic foot ulceration), can be lowered under safety thresholds by selecting a specific optimal muscle coordination pattern during gait. The proposed research will advance the computational environment at the Stanford Center for Biomedical Computation by providing basic surrogate modeling algorithms that are potentially applicable to other multiscale physics-based problems and also extend the Center’s efforts in neuromuscular biomechanics. | |
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Registered: 2006-09-01 17:19 |
Evertor and invertor muscle co-activation prevents ankle inversion injury
- The study described in this publication used musculoskeletal simulations to compare the capacity of planned invertor/evertor co-activation versus stretch reflexes with physiologic delay to prevent ankle inversion injuries. To achieve this, developed a novel model, muscle stretch controllers, and muscle reflex controllers for simulating landing in OpenSim. By freely providing the models, software plugins defining the controllers, and the resulting simulations, we hope to enable others to answer questions about landing control and injuries using simulations.
All models, data, and simulation results are provided in the downloads area of this project.
For software and sourcecode defining the novel stretch feedback controller and stretch reflex controller, see the related repository on GitHub.
https://github.com/msdemers/opensim-reflex-controllers
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Activity Percentile: 38.17 Registered: 2015-07-20 20:18 |
OpenSim plugin to extract the muscle lines of action
- The OpenSim plugin made available with this project extends the functionality of OpenSim and allows the user to extract the directionality of the muscle lines of action for a given kinematics. Also the muscle attachments can be exported if required by the user.
With this information it is generally possible to define loads representative of the muscle forces in finite element models of bone structures.
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Registered: 2012-04-22 20:49 |
49 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3>