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127 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
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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 |
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 |
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 |
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: 95.42 Registered: 2009-07-14 23:24 |
Muscle-actuated Simulation of Human Running
- The purpose of this study was to determine how muscles contribute to propulsion (i.e., the fore-aft acceleration) and support (i.e., the vertical acceleration) of the body mass center during running at 3.96 m/s (6:46 min/mile), including the effects of the torso and arms. To achieve this, we developed a three-dimensional muscle-actuated simulation of running that included 92 musculotendon actuators representing 76 muscles of the lower extremities and torso. By using a three-dimensional model with lower extremity muscles, a torso, and arms, we were able to quantify the contribution of muscles and arm dynamics to mass center accelerations in three dimensions, which provided insights into the actions of muscles during running. The simulation is freely available (simtk.org) allowing other researchers to reproduce our results and perform additional analyses. | |
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Registered: 2010-06-04 01:25 |
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: 93.89 Registered: 2015-09-15 17:52 |
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: 93.51 Registered: 2012-06-11 22:52 |
Simulations of Crouch Gait
- This research examined the <b>dynamics of crouch gait among children with cerebral palsy </b>. Specifically, our work examined individual muscles contribute to joint and mass center movement in children with cerebral palsy who walk with a crouch gait. In 2010, we created simulations of single-limb stance for 10 subjects with a mild crouch gait. In 2012-2013, we expanded this study to evaluate muscle contributions to gait during mild, moderate, and severe crouch gait. We also used these simulations to evaluate how muscle weakness may contribute to crouch gait and to examine knee contact force during crouch gait. In 2017, these simulations were also used to evaluate how passive or powered ankle foot orthoses may assist during crouch gait. Together this research has helped us understand the mechanisms that contribute to crouch gait and guide treatment planning to improve gait for children with cerebral palsy.
Please visit the <a href="https://nmbl.stanford.edu"> Neuromuscular Biomechanics Lab </a> and the <a href="depts.washington.edu/uwsteele/"> Ability & Innovation Lab </a> to learn more about our on-going research in this area.
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Activity Percentile: 92.37 Registered: 2010-05-18 22:21 |
Upper Extremity Dynamic Model
- The project releases the MoBL-ARMS dynamic musculoskeletal model of the human upper extremity, implemented in SIMM/SDFast and OpenSIM. Please see the model summary for details of the new model and its use.
New! We have released a new version of the OpenSim models and tutorial, now compatible with releases 3.2 and later. See download page for release and more information. | |
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Activity Percentile: 91.98 Registered: 2011-08-02 19:56 |
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 |
Upper Extremity Kinematic Model
- The project holds all the files necessary for a SIMM-based kinematic musculoskeletal model of the human upper-extremity which can also be easily imported and used in OpenSIM. In order to respect the time and effort put in by the original developers please carefully read accompanying publications and cite appropriate references in future work. The links to the left contain all the files (Downloads) and documentation (Documents) related to the model.
<hr> </hr>
<b>Please cite the following paper:</b>
- Holzbaur KR, Murray WM, Delp SL.: A model of the upper extremity for simulating musculoskeletal surgery and analyzing neuromuscular control., Ann Biomed Eng. 2005 Jun;33(6):829-40. (2005)
<hr> </hr>
<b>About the model:</b>
This model of the upper extremity includes 15 degrees of freedom representing the shoulder, elbow, forearm, wrist, thumb, and index finger, and 50 muscle compartments crossing these joints. The kinematics of each joint and the force-generating parameters for each muscle were derived from experimental data. The model estimates the muscle–tendon lengths and moment arms for each of the muscles over a wide range of postures. Given a pattern of muscle activations, the model also estimates muscle forces and joint moments. The moment arms and maximum moment generating capacity of each muscle group (e.g., elbow flexors) were compared to experimental data to assess the accuracy of the model. These comparisons showed that moment arms and joint moments estimated using the model captured important features of upper extremity geometry and mechanics. The model also revealed coupling between joints, such as increased passive finger flexion moment with wrist extension.
<hr> </hr> | |
Registered: 2008-07-25 21:56 |
IA-FEMesh
- In an effort to facilitate anatomic FE model development, we introduce IA-FE Mesh (Iowa FE Mesh), a freely available software toolkit. IA-FEMesh employs a multiblock meshing scheme aimed at hexahedral mesh generation. An emphasis has been placed on making the tools interactive, in an effort to create a user-friendly environment. The goal is to provide an efficient and reliable method for model development, visualization, and mesh quality evaluation. While these tools have been developed, initially, in the context of skeletal structures, they can be applied to a virtually endless number of modeling applications. | |
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Activity Percentile: 89.31 Registered: 2008-08-29 02:59 |
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: 88.55 Registered: 2015-01-14 23:10 |
Matlab-Opensim Interfaces
- Matlab is a common analysis tool used for data manipulation, signal processing and function integration. These features can be used in conjunction with simulation tools provided by the Opensim interface.
This project provides tools for using different aspects of Opensim within the Matlab environment. This includes 1) using the command line tools by generating XML setup files etc (Scaling, Inverse Kinematics, Inverse Dynamics, Forward Dynamics) 2) using the Java classes that the Opensim GUI is built on to access aspects of the Opensim API.
Provided in this project are -
1) Tools for taking motion capture data from C3D files and generating the required input files (marker files {*.trc} motion files {*.mot}, GRF xml files {*.xml}) as well as setup files for each of the different tools that can be called from the command line. Example data from different models and data sets are provided including example pipelines to analyse data using Opensim. Some of this implementation has taken inspiration from Tim Dorn's excellent GaitExtract toolbox. A new page with more up-to-date tools can be found here - http://simtk-confluence.stanford.edu:8080/display/OpenSim/Tools+for+Preparing+Motion+Data
2)Matlab functions and example scripts for accessing the Opensim API through Matlab. This utilises the Java wrapping classes that the Opensim GUI is built on. Examples are shown to open and edit models as well as perform a 'Muscle Analysis'. Please now use the inbuilt support from Opensim rather than this toolbox! (http://simtk-confluence.stanford.edu:8080/display/OpenSim/Scripting+with+Matlab) | |
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Activity Percentile: 85.11 Registered: 2011-08-06 20:22 |
OpenSim Advanced Users Workshop, August 12-14, 2009
- This workshop covers advanced topics in OpenSim, an easy-to-use, extensible software for modeling, simulating, controlling, and analyzing the neuromusculoskeletal system. The workshop is an opportunity to learn more about how OpenSim works "under the hood" and get supervised, hands-on assistance with problems participants bring to the workshop. On the first day, a conceptual overview of OpenSim will be provided. The second and third days will be devoted to working on problems participants bring to the workshop. Participants have the opportunity to work in small breakout groups with OpenSim experts on their research problems. | |
Registered: 2009-08-07 22:39 |
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 |
MB Knee: Multibody Models of the Human Knee
- The purpose of this site is to disseminate geometry and modeling information for development of knee models, primarily in the multibody framework. MBKnee_4 is based on in vivo measurements from a 29 year old female while MBKnee_1, MBKnee_2, and MBKnee_3 are based on cadaver knees that were physically tested in a dynamic knee simulator. Knee geometries (bone, cartilage, and mensici) were derived from Magnetic Resonance Imaging (MRI) and ligament insertions come from MRI, the literature, and probing the cadaver knees. The site also contains information on ligament modeling, such as bundle insertion locations and zero load lengths. Examples of knee models are also provided in the form of ADAMS command files. MBKnee_4 is the most recent model and it includes representation of the medial and lateral menisci, wrapping around bone and cartilage of the meniscal horn attachments, attachments of the deep medial collateral ligament and the anterolateral ligament to the menisci, representation of the posterior oblique ligament and the anterolateral ligament, ligament zero load lengths (or reference strain) determined from experimental laxity measurements, and measured motion to deep flexion.
Funding for this work was provided by the National Institute of Arthritis an Musculoskeletal and Skin Diseases (RAR061698) and by the National Science Foundation (CMS-0506297). | |
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Activity Percentile: 79.77 Registered: 2012-05-25 17:31 |
Musculoskeletal Model of the Lumbar Spine
- The work here features a number of different OpenSim models of the lumbar spine developed to study lumbar kinematics and dynamics.
Briefly, the models consist of the following bodies:
# rigid pelvis and sacrum
# five lumbar vertebrae (separated by joints with three rotational degrees of freedom)
# torso (thoracic spine + ribcage)
The motion of the individual joints are defined using constraint functions specifying the motion of the lumbar vertebra as functions of the net lumbar motion (flexion-extension, lateral bending and axial rotation). Future models will incorporate joints with stiffness properties to more accurately mimic the action of the intervertebral joints.
The most complex of these models also feature the 238 muscle fascicles associated with the 8 main muscle groups of the lumbar spine necessary to study the contribution of the lumbar spinal musculature to spinal motion. Simpler models incorporating two and seven of the main muscle groups of the lumbar spine are provided as well for completeness.
Read more about the model in the paper, freely downloadable at http://link.springer.com/article/10.1007%2Fs10237-011-0290-6.
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September 2011 Addendum
Click on the "Downloads" link to the left for downloads related to more recent work.
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September 2012 Addendum
The Constrained Lumbar Spine Model does not require any of the files uploaded after the creation of the Constrained Lumbar Spine Model project. The .vtp files (and descriptions) are included here for the benefit of those of you who wish to create your own model that has origins shifted to the center of the bones since this typically saves a number of transformations. Many apologies for any confusion(!).
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March 2014 Addendum
(1)
This model was build with OpenSim 2+. Version 3+ will not allow you to use periods (.) in your variable names. Unfortunately, a bunch of the variables used (muscles mainly) have periods in the names so it will throw an error if you try and run it in OpenSim version 3+. To fix this, either use version 2+, OR, rename the variables appropriately.
(2)
We have all graduated and are no longer actively working on this project (we haven't been working on it since the end of 2011 actually). At this point, you probably know more than us about OpenSim so we apologize in advance if our support is subpar.
(3)
The complex mode is not meant to be run straight out of the box. It has almost 250 muscles after all and unless you have a super computer, running CMC, or FD on it is going to bring up the rainbow ball of death on your computer.
Rather, it's meant to be a reference for those of you who intend to build up your own model. My advice would be to start with the simple 4 fascicle model, get it to work, then incrementally build up from there using the parameters provided in our model as a starting point. Copy-Paste is your friend here. :)
(4)
If this is your very first OpenSim project, I strongly _strongly_ *strongly* suggest that you go through the examples provided with the OpenSim version you just downloaded and understand how they work. This will save you months of pain down the road. | |
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Activity Percentile: 79.39 Registered: 2010-11-04 02:25 |
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 |
127 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4> <5> <6> <7>