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86 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4> <5>
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 |
Open Knee(s): Virtual Biomechanical Representations of the Knee Joint
- Open Knee(s) was aimed to provide free access to three-dimensional finite element representations of the knee joint (<A HREF="https://doi.org/10.1007/s10439-022-03074-0">https://doi.org/10.1007/s10439-022-03074-0</A>). The development platform remains open to enable any interested party to use, test, and edit the model; in a nut shell get involved with the project.
This study was primarily funded by the National Institute of General Medical Sciences, National Institutes of Health (R01GM104139) and in part by National Institute of Biomedical Imaging and Bioengineering (R01EB024573 and R01EB025212). Previous activities leading towards this project had been partially funded by the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (R01EB009643).
Open Knee(s) by Open Knee(s) Development Team is licensed under a <A HREF="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</A>.
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Registered: 2010-02-18 20:41 |
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 |
OpenArm: Volumetric & Time Series Models of Muscle Deformation
- We invite anyone in the research community to use the OpenArm and OpenArm Multisensor data sets to validate existing muscle deformation models or to devise new ones.
Full details can be found in the following papers:
Laura A. Hallock, Bhavna Sud, Chris Mitchell, Eric Hu, Fayyaz Ahamed, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Toward Real-Time Muscle Force Inference and Device Control via Optical-Flow-Tracked Muscle Deformation." In IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). IEEE, 2021. (Under review.)
Laura Hallock, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Muscle deformation correlates with output force during isometric contraction." In IEEE RAS/EMBS International Conference on Biomedical Robotics & Biomechatronics (BioRob). IEEE, 2020. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2020biorob.)
Yonatan Nozik*, Laura A. Hallock*, Daniel Ho, Sai Mandava, Chris Mitchell, Thomas Hui Li, and Ruzena Bajcsy, "OpenArm 2.0: Automated Segmentation of 3D Tissue Structures for Multi-Subject Study of Muscle Deformation Dynamics," in International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, 2019. *Equal contribution. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/nozikhallock2019embc.)
Laura Hallock, Akira Kato, and Ruzena Bajcsy. "Empirical quantification and modeling of muscle deformation: Toward ultrasound-driven assistive device control." In IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2018icra.)
This project is currently in development in the Human-Assistive Robotic Technologies (HART) Lab at the University of California, Berkeley (http://hart.berkeley.edu). | |
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Registered: 2018-11-28 20:40 |
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: 95.08 Registered: 2015-09-15 17:52 |
SimVascular: Examples and Clinical Cases
- We invite you to download and try these examples and clinical case projects, which are all compatible with the open source SimVascular cardiovascular modeling software package. Each case includes image data of a healthy or diseased individual, a 3D anatomic model created from the image data, and simulation job files which specify initial conditions, boundary conditions and various parameters required to run the simulation. Many of the cases are already organized as SV projects, which means you can easily load them into SimVascular and view or try out various project components. Following the guides in the SimVascular documentation website, you can also create new models and run simulations with different conditions, based on these example cases.
You are free to download the examples and cases provided that you properly reference the source. The cases are part of the academic output of the researcher cited and should be referred to as such. Permission is granted to use these cases for research purposes, but for commercial use please contact the director of the Cardiovascular Biomechanics Computation Lab, Alison Marsden (amarsden@stanford.edu).
The examples and clinical cases included are:
Example: Demo Project
Example: Cylinder Project (no image, for simulation)
Clinical Case: Coronary Normal
Clinical Case: Aortofemoral Normal 1
Clinical Case: Aortofemoral Normal 2
Clinical Case: Healthy Pulmonary
SimVascular is available for download at our project website at:
https://simtk.org/projects/simvascular
Comprehensive documentation is available on the SimVascular website at:
http://www.simvascular.org
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Activity Percentile: 94.70 Registered: 2014-03-14 20:12 |
Full Body Model for use in Dynamic Simulations of Human Gait
- Our paper describes a full body OpenSim model with musculotendon parameters derived from experimental measurements of 21 cadaver lower limbs and magnetic resonance images of 24 young adult subjects. Our model is derived from the lower body model published by Arnold et al. (2010) and the tracking upper body by Hamner et al. (2013), but updates the muscle force distribution to reflect those of a young, healthy population, includes a new knee model to accurately represent internal forces, and simplified muscle wrapping surfaces to increase computation speed in CMC and other muscle-driven simulations. | |
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Activity Percentile: 93.56 Registered: 2012-06-11 22:52 |
Are subject-specific musculoskeletal models robust to parameter identification?
- This study analyzed the sensitivity of the predictions of an MRI-based musculoskeletal model (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the unavoidable uncertainties in parameter identification, i.e., body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. | |
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Activity Percentile: 92.80 Registered: 2014-11-10 15:19 |
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 |
Grand Challenge Competition to Predict In Vivo Knee Loads
- Knowledge of muscle and joint contact forces during gait is necessary to characterize muscle coordination and function as well as joint and soft-tissue loading. Musculoskeletal modeling and simulation is required to estimate muscle and joint contact forces, since direct measurement is not feasible under normal conditions. This project provides the biomechanics community with a unique and comprehensive data set to validate muscle and contact force estimates in the knee. This data set includes motion capture, ground reaction, EMG, tibial contact force, and strength data collected from a subject implanted with an instrumented knee prosthesis. | |
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Activity Percentile: 90.91 Registered: 2009-07-14 23:24 |
Model of the Scapulothoracic Joint
- In this study, we developed a rigid-body model of a scapulothoracic joint to describe the kinematics of the scapula relative to the thorax. This model describes scapula kinematics with four degrees of freedom: 1) elevation and 2) abduction of the scapula on an ellipsoidal thoracic surface, 3) upward rotation of the scapula normal to the thoracic surface, and 4) internal rotation of the scapula to lift the medial border of the scapula off the surface of the thorax. The surface dimensions and joint axes can be customized to match an individual’s anthropometry. We compared the model to “gold standard” bone-pin kinematics collected during three shoulder tasks and found modeled scapula kinematics to be accurate to within 2 mm root-mean-squared error for individual bone-pin markers across all markers and movement tasks. As an additional test, we added random and systematic noise to the bone-pin marker data and found that the model reduced kinematic variability due to noise by 65% compared to Euler angles computed without the model. Our scapulothoracic joint model can be used for inverse and forward dynamics analyses and to compute joint reaction loads. The computational performance of the scapulothoracic joint model is well suited for real-time applications, is freely available as an OpenSim 3.2 plugin, and is customizable and usable with other OpenSim models. | |
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Activity Percentile: 88.64 Registered: 2015-01-14 23:10 |
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 |
Dynamic Arm Simulator
- This project aims to develop a musculoskeletal model for the real-time, dynamic simulation of arm movement. It features a large-scale model of the shoulder and elbow, including the joints of the shoulder girdle and scapulo-thoracic contact. The simulation is implemented using a Matlab MEX function and uses OpenSim for pre-processing and visualisation. | |
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Registered: 2008-07-24 18:10 |
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 |
Delft Shoulder and Elbow Model
- This project is for development and support for users of the Delft Shoulder and Elbow Model, a large-scale, 3D musculoskeletal model. Development is ingoing, with a number of enhancements since the original description in van der Helm (1994), and the model has been widely used. | |
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Registered: 2009-12-04 10:32 |
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: 77.27 Registered: 2011-08-05 01:17 |
Cal Poly Human Motion Biomechanics Lab Knee Joint Finite Element Model
- This project offers a subject-specific, total knee joint finite element model. In the MS thesis associated with this project, the model is used to predict articular cartilage stress and strain during the stance phase of gait. The model was partially validated with in vivo and other finite element analyses, but requires further validation and development to accurately predict articular cartilage contact parameters. Specific limitations include material properties, as well as potentially loading boundary conditions. Special attention should be paid to the "Future Work" section of the referenced thesis document in order to further develop the model for use in other studies. | |
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Activity Percentile: 73.86 Registered: 2014-07-23 03:48 |
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: 70.45 Registered: 2013-02-19 05:59 |
86 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4> <5>