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100 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 |
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 |
Reproducibility in simulation-based prediction of natural knee mechanics
- Modeling and simulation offers a cost-effective and prompt path to respond to the pressing medical needs for restoration of knee function. However, the reproducibility of simulation results, to inform scientific and clinical decision making, is questionable. Reproducibility is a pressing issue in scientific conduct. For modeling and simulation, there is added scrutiny particularly with the desire to repurpose and reuse virtual specimens for prospective solutions of diverse scientific and clinical problems. A significant portion of the modeling and simulation workflow includes development, evaluation, and simulation. This workflow, while based on objective scientific principles, commonly requires intuition during implementation; therefore relies on the knowledge and expertise of the modeler. This ‘art of modeling’ can be a fundamental source of diminished reproducibility. The goal of this study is to understand how modelers’ choices to build models, even when using the same data, may influence predictions and therefore the reproducibility of simulation results. Five modeling and simulation teams will independently develop, calibrate and benchmark computational models of knees based on the same data sets and reuse these models to simulate the same scientifically and clinically relevant scenarios. Ideally, predicted joint and tissue mechanics will be the same. In practice, the skills and experiences of model developers will reflect upon their modeling choices; and as a result, discrepancies will exist. The proposed activity will document the magnitude and potential sources of such discrepancies through comparisons of model components and simulation results. This project will examine and critique the current state of model development and simulation reproducibility in joint and tissue mechanics. This will translate into reliable models of the knee joint for simulation-based discoveries and in silico design and evaluation of medical devices and interventions. The required exchange of data, model components, and simulation results among the teams and with the public will also impact developers and users of such resources. Specifications, to facilitate data and model exchange and to develop data and modeling standards, and guidance, to inform modeling and simulation workflows, will likely emerge as by-products of the research activity. Subsequently, this project aims to curate various modeling & simulation and data resources for scientific and clinical investigations of knee biomechanics. An additional goal of the project site is to be a discussion platform among investigators who collect data and build models for the knee joint. | |
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Registered: 2015-12-07 21:06 |
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: 94.66 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: 92.37 Registered: 2012-06-11 22:52 |
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 |
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: 89.31 Registered: 2015-01-14 23:10 |
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: 88.93 Registered: 2009-07-14 23:24 |
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 |
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 |
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 |
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 |
Validation of Subject-Specific Knee Models from In Vivo Measurements
- Working models, data, code, and results for work to validate that in vivo methods for measuring laxity and obtaining knee geometry are comparable to methods previously standard for knee modeling of in vitro specimens.
This dataset is part of an ongoing manuscript to validate that sources of data from currently available in vivo methods are sufficient to create computational models of the knee compared with existing in vitro techniques. The data included in this repository is for the S192803 specimen of that dataset and includes experimental data, working models, code, and results obtained for that model and used in that manuscript.
The dataset contains experimental data, models, code, and results for the S192803 specimen data. This dataset is one of two model datasets used in the paper Validation of Subject-Specific Knee Models from In Vivo Measurements, which is in review at the Journal of Biomechanical Engineering. The dataset contained herein is derived from the experimental data collected during a previous publication in the Journal of Medical Devices, entitled: "Apparatus for In Vivo Knee Laxity Assessment Using High-Speed Stereo Radiography". Available at: https://doi.org/10.1115/1.4051834
A similar dataset exists for the other specimen, S193761.
Work was created by Dr. Thor E. Andreassen, Dr. Donald R. Hume, Dr. Landon D. Hamilton, Stormy L. Hegg, Sean E. Higinbotham, and Dr. Kevin B. Shelburne at the Center for Orthopaedic Biomechanics at the University of Denver.
The work was funded by the NIH National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institute of Biomedical Imaging and Bioengineering, and the National Institute of Child Health and Human Development (Grant U01 AR072989).
If you have any questions, please email the main author, Dr. Thor Andreassen, at thor.andreassen@du.edu
Sharing/USE
This Code/Software is free to use for any reason. However, we ask that if you use any part of this work, that you cite the original two works that made it possible:
Andreassen, T. E., Hamilton, L. D., Hume, D., Higinbotham, S. E., Behnam, Y., Clary, C., and Shelburne, K. B. (September 10, 2021). "Apparatus for In Vivo Knee Laxity Assessment Using High-Speed Stereo Radiography." ASME. J. Med. Devices. December 2021; 15(4): 041004. https://doi.org/10.1115/1.4051834
Andreassen, T. E., Hume, D. R., Hamilton, L. D., Hegg, S.L., Higinbotham, S. E., and Shelburne, K. B. "Validation of Subject-Specific Knee Models from In Vivo Measurements." ASME. J. Biomech, Engineering.
Liability Agreement
The Data is provided “as is” with no express or implied warranty or guarantee. The University of Denver and the Center for Orthopaedic Biomechanics do not accept any liability or provide any guarantee in connection with uses of the Data, including but not limited to, fitness for a particular purpose and noninfringement. The University of Denver and the Center for Orthopaedic Biomechanics are not liable for direct or indirect losses or damage, of any kind, which may arise through the use of this data. | |
Registered: 2023-12-12 23:13 |
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 |
Hip Musculoskeletal Model
- The purpose of this project was to create a detailed model of the muscles spanning the hip joint. Please see descriptions specific to each iteration of the model in Downloads.
2398Hip_w_LaiArnold - Please cite: Song K, Gaffney BMM, Shelburne KB, Pascual-Garrido C, Clohisy JC, Harris MD. Dysplastic hip anatomy alters muscle moment arm lengths, lines of action, and contributions to joint reaction forces during gait. J Biomech. 2020 Sep 18;110:109968. PMID: 32827786; PMCID: PMC7737424.
2396Hip - Please cite: Harris MD, MacWilliams BA, Bo Foreman K, Peters CL, Weiss JA, Anderson AE. Higher medially-directed joint reaction forces are a characteristic of dysplastic hips: A comparative study using subject-specific musculoskeletal models. J Biomech. 2017 Mar 21;54:80-87. PMID: 28233552; PMCID: PMC5939935.
Hip_23_72 - Please cite: Shelburne, K.B., Decker, M.J., Krong, J., Torry, M.R., Philippon, M.J., 2010. Muscle forces at the hip during squatting exercise. In: 56th Annual Meeting of the
Orthopaedic Research Society. New Orleans, LA
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Registered: 2010-08-09 18:00 |
100 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4> <5>