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14 projects in result set.
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 |
Statistical Shape Model of the Tibia
- This project provides a freely accessible three-dimensional statistical shape model (SSM) of the tibia, the MATLAB scripts for generating a SSM and the segmented surface models of the cortical and trabecular bone. Information on the use of code and data can be found in the read-me file contained within the download.
Further, this dataset and associated statistical shape models can be used in several ways to assist with skeletal focused research of the tibia-fibula. We do not have the scope to highlight each and every potential application, however have provided a series of example cases of where and how the shape models may be used. Our hope is that these examples can be directly used, or assist in guiding other uses.
Case 1: Generating Surface Samples — this example case demonstrates how to use the shape model data to reconstruct a randomly sampled 'population' of surfaces.
Case 2: Predicting and Generating Trabecular Volumes — this example case demonstrates how to combine the tibia and trabecular shape models to predict and generate the trabecular volume from a tibial surface.
Case 3: Generating Tibia-Fibula Surfaces from Landmarks — this example case demonstrates how to use the tibia-fibula shape model to estimate and reconstruct surfaces from palpable landmarks on the tibia and fibula.
Please cite our work if you use this code or data.
<iframe src="https://widgets.figshare.com/articles/20454462/embed?show_title=1" width="568" height="351" allowfullscreen frameborder="0"></iframe> | |
Registered: 2021-07-05 07:11 |
CoBi Core Models, Data, Training Materials
- This project contains a variety of materials from Computational Biomodeling (CoBi) Core of the Cleveland Clinic, relevant to physics-based simulation of the biomechanical system. These may include various published/unpublished models, data, and training material generated through various small projects. | |
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Registered: 2010-10-07 13:09 |
Fiber Tractography for Finite-Element Modeling of Transversely Isotropic Tissues
- This project demonstrates the process for fiber tractography of complex biological tissues with transverse isotropy, such as tendon and muscle. This is important for finite element studies of these tissues, as the fiber direction must be specified in the constitutive model. This project contains code, models, and data that can be used to reproduce the results of our publication on this technique. The supplied instructional videos will enable researchers to easily and efficiently apply this method to a variety of other tissues. The software used in the fiber tractography process and demonstrated in this project is Matlab, Autodesk Inventor (free for educators), and Autodesk Simulation CFD (free for educators). Full demonstrations and process instructions can be found in the 7 videos posted at https://vimeo.com/album/3414604:
Contents:
Chapter 1: Introduction (2:35)
This video introduces the CFD fiber tractography software pipeline
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Chapter 2: Supplementary materials code, models and data (20:21)
This video shows the shared models, code, and data posted online at simtk.org/m3lab_cfd4fea.
Chapter 3: Finite element simulations (5:38)
This video shows finite element simulations using the fiber mapping process.
Chapter 4: Iliacus example walkthrough (21:38)
This video shows the step-by-step process for fiber mapping the iliacus muscle (a hip flexor).
Chapter 5: Bflh example walkthrough (12:09)
This video shows the step-by-step process for fiber mapping the biceps femoris longhead muscle (a hamstring).
Chapter 6: Autodesk Inventor segmentation (9:09)
This video shows how to do segmentation of medical images in Autodesk Inventor in order to simplify the solid model for the CFD and FEA software.
Chapter 7: Curved inlet surfaces (6:28)
This video shows how to create curved inlet surfaces for use in Autodesk Simulation CFD. | |
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Activity Percentile: 36.64 Registered: 2015-05-28 18:52 |
Wrist Anatomy and Kinematics Data Collection
- <div align="justify">CT images of wrists from 90 healthy volunteers (43 males and 47 females) were acquired in various wrist positions. The outer cortical surfaces of the carpal bones, radius, and ulna in a 3D format, and each bone kinematics were calculated for each wrist position using a methodology described in the README file associated with the database. The database does not include soft tissue or the cartilage information of the wrist. Moreover, there is a MATLAB graphic user interface (GUI) available for you to observe the database. This dataset comes from four different NIH funding between 2001 and 2014.</div>
Please cite the work if you're using this database:
<div align="justify"><a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/jor.24435">Akhbari, B., Moore, D. C., Laidlaw, D. H., Akelman, E., Weiss, A-P. C., Wolfe, S. W., Crisco, J. J., 2019. Predicting Carpal Bone Kinematics using an Expanded Digital Database of Wrist Carpal Bone Anatomy and Kinematics, Journal of Orthopaedic Research. DOI:10.1002/jor.24435</a></div>
If you want the pdf version of the manuscript, please send your request on <a href="http://bit.ly/2YU2tTh">ResearchGate</a>.
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Registered: 2019-02-25 19:48 |
Data and Media Management for Biomechanics (DMMB)
- (written for biomechanics researchers interested in managing and distributing big data/ media)
This project will serve as a tool to help researchers categorize, organize, prioritize, and distribute big data collected specifically in biomechanical applications. Additionally, this project will serve as a project map a guide for how to streamline and distribute biomechanics-related media (photographs, videos, interactive modules, etc.). | |
Registered: 2014-02-04 18:53 |
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 |
Application for the simulation of the prosthetic gait
- This application has a dataset belonging to macha prosthetic patterns , in which the angle of the socket and prosthetic foot is changed.
It focuses on patients with transtibial amputation and uses opensim in MATLAB libraries to link and generate a model for opensim , based on data captured from a measuring TECHNAID brand. | |
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Registered: 2016-08-24 14:21 |
CCIvsJointStiffness
- Muscle co-contraction generates joint stiffness to improve stability and accuracy during limb movement but at the expense of higher energetic cost. However, quantification of joint stiffness is difficult using either experimental or computational means. In contrast, quantification of muscle co-contraction using an EMG-based Co-Contraction Index (CCI) is easier and may offer an alternative for estimating joint stiffness. This study investigated the feasibility of using two common CCI’s to approximate lower limb joint stiffness trends during gait.
Please cite the following paper:
G. Li, M.S. Shourijeh, D. Ao, C. Patten, B.J. Fregly, How Well Do Commonly Used Co-Contraction Indices Approximate Lower Limb Joint Stiffness Trends during Gait?, Frontiers in Bioengineering and Biotechnology, 2020, DOI: 10.3389/fbioe.2020.588908 | |
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Registered: 2020-10-31 05:04 |
C++ and Python code, distributed computing and OpenMM interfaces for simulations
- please cite: "Interplay of Protein and DNA Structure Revealed in Simulations of the lac Operon" (PLOS One 2013)
for any code related to protein-DNA modeling and
"Free Energy Monte Carlo Simulations on a Distributed Network" (Lecture Notes in Computer Science Journal for PARA 2010)
http://link.springer.com/chapter/10.1007%2F978-3-642-28145-7_1
for parallel client-server code, users of additional code should cite this web site. Code is provided as-is with no warranty and examples are provided to illustrate the usage of these modeling techniques with some sample systems. Code is the intellectual property of Luke Czapla, developer and biophysicist. Examples are provided in C/C++ and Python. | |
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Activity Percentile: 0.00 Registered: 2014-02-01 22:32 |
Muscle function of overground running across a range of speeds
- This project is a repository of overground running data (3.5m/s 5.2m/s, 7.0m/s and 9.0m/s) along with a working musculoskeletal model to perform simulations and derive the function of individual muscles. | |
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Registered: 2011-08-07 14:01 |
Probabilistic Tool for Considering Patient Populations & Model Uncertainty
- The goal of this project is to develop a generalized, probabilistic plugin for OpenSim and to demonstrate subject-specific and population-based applications of this tool. The tool will implement two probabilistic methods (Monte Carlo and advanced mean value) and provide a user-friendly interface to create analyses and visualize results. The probabilistic tool will quantify 5 to 95% confidence bounds for output measures and sensitivity factors, which are used to identify the most important input parameters that contribute to output variability. A subject-specific model will be used to account for measurement errors associated with motion capture and input parameter uncertainties. The code is currently written in Matlab but future releases and additions will explore other applications. | |
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Activity Percentile: 0.00 Registered: 2013-08-30 19:54 |
Ribosomal translocation with EF-G
- This project aims at providing new insight about RNA translation into protein, focusing on the translocation step induced by Elongation Factor G (EF-G). In the past few years, biologists provided high-resolution structures of key steps of the process. Our goal is to compute a trajectory of the translocation at atomic level using an accurate morphing technique. | |
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Activity Percentile: 0.00 Registered: 2014-07-23 13:04 |
Synergy Optimization
- These MATLAB codes are an implementation of a novel approach for estimating muscle forces/activations by imposing a synergy structure within optimization (termed “synergy optimization,” or SynO). For comparison, users can switch to a MATLAB implementation of a static optimization in the code. Sample experimental overground walking data obtained from the first knee grand challenge competition are also included. For more details about this study and project, read the following paper:
Shourijeh, Mohammad S., and Benjamin J. Fregly. "Muscle Synergies Modify Optimization Estimates of Joint Stiffness During Walking." Journal of Biomechanical Engineering 142.1 (2020). | |
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Registered: 2020-08-30 05:11 |