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77 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4>
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 |
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 |
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: 94.66 Registered: 2009-07-14 23:24 |
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: 93.89 Registered: 2010-05-18 22:21 |
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: 88.17 Registered: 2015-01-14 23:10 |
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: 87.02 Registered: 2010-11-04 02:25 |
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 |
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 |
Muscle contributions to mass center accelerations over a range of running speeds
- These simulations were created using OpenSim and the workflow included Scale, Inverse Kinematics (IK), Reduced Residual Algorithm (RRA), Computed Muscle Control (CMC), and Induced Acceleration Analysis (IAA). The following resources provide instructions for using these tools and information on how to generate and evaluate musculoskeletal simulations:
• OpenSim User's Guide | http://stanford.io/17cia3U
• OpenSim Support Webpage | http://stanford.io/17ciwrn
• Webinar on Simulations of Running | http://bit.ly/oDIUOa
<object width="500" height="375"><param name="allowfullscreen" value="true" /><param name="allowscriptaccess" value="always" /><param name="movie" value="//vimeo.com/moogaloop.swf?clip_id=45852110&force_embed=1&server=vimeo.com&show_title=1&show_byline=1&show_portrait=1&color=00adef&fullscreen=1&autoplay=0&loop=0" /><embed src="//vimeo.com/moogaloop.swf?clip_id=45852110&force_embed=1&server=vimeo.com&show_title=1&show_byline=1&show_portrait=1&color=00adef&fullscreen=1&autoplay=0&loop=0" type="application/x-shockwave-flash" allowfullscreen="true" allowscriptaccess="always" width="500" height="375"></embed></object> <p><a href="http://vimeo.com/45852110">Muscle contributions to fore-aft and vertical body mass center accelerations over a range of running speeds</a> from <a href="http://vimeo.com/samner">Sam Hamner</a> on <a href="http://vimeo.com">Vimeo</a>.</p>
The goal of this study was to determine how muscles and arm swing affect dynamics of the body at different running speeds. Specifically, we determined how muscles contribute to mass center accelerations during the stance phase of running, and how the arms act to counterbalance the motion of the legs. We achieved this goal by creating and analyzing muscle-driven, forward dynamic simulations of ten subjects running across a range of speeds: 2 m/s, 3 m/s, 4 m/s, and 5 m/s. An induced acceleration analysis determined the contribution of each muscle to mass center accelerations. Our simulations also included arm motion, allowing us to investigate the contributions of arm swing to running dynamics. These simulations use experimental data as inputs, so we also collected data to characterize joint angles, joint moments, and ground reaction forces at different running speeds. | |
Activity Percentile: 80.53 Registered: 2011-01-28 22:11 |
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 |
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 |
Simulated Assistive Devices for Loaded Walking
- This project contains experimental data and muscle-actuated tracking simulations of male subjects walking while carrying heavy load, and OpenSim simulations of these subjects wearing hypothetical ideal assistive devices. We collected motion capture data of 7 subjects walking in 4 different conditions: walking (a) without load at a freely selected speed, (b) without load at 80% of the freely selected speed, (c) while carrying 38 kg on the torso at a new freely selected speed, and (d) while carrying 38 kg at the same speed as in (a).
Based on the simulations of loaded walking (condition (c) above), we created new simulations to predict the effect of ideal assistive devices on the metabolic cost of walking. We examined 7 massless devices that each provided unrestricted torque at one degree of freedom and in one direction: hip abduction, hip flexion, hip extension, knee flexion, knee extension, ankle plantarflexion, and ankle dorsiflexion. We estimated the optimal device torques, and the devices' effect on metabolic cost and muscle activity.
Dembia CL, Silder A, Uchida TK, Hicks JL, Delp SL (2017) Simulating ideal assistive devices to reduce the metabolic cost of walking with heavy loads. PLoS ONE 12(7): e0180320. https://doi.org/10.1371/journal.pone.0180320 | |
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Registered: 2016-05-07 02:08 |
Stroke gait
- This project involves the generation of subject-specific simulations of a range of post-stroke hemiparetic gait patterns, contribution of parallel optimization techniques, comparison of control algorithms, and analysis of 2d and 3d results. | |
Activity Percentile: 62.60 Registered: 2006-08-23 17:28 |
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: 59.16 Registered: 2012-05-25 17:31 |
Analysis of arm swing during human walking
- This project provides a simplified version of the UpperLowerBodySimple model from the ULB-project, which was adjusted with the purpose to decrease the run time of the simulations.
The adjusted model was used to determine arm swing kinematics (with and without muscle excitations) during human walking, with arm movements not exceeding 70 degrees of anteflexion or abduction. However, the adjusted_ULB model can be used for modeling and simulating kinematics and kinetics of all neuromusculoskeletal systems.
For an example of an arm swing simulation without muscle excitation we refer to the video below.
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Activity Percentile: 57.25 Registered: 2013-10-19 09:43 |
Simulated muscle fiber lengths and velocities during walking and running
- This project contains models and simulation results for the subjects included in the attached publication. | |
Registered: 2012-06-03 19:50 |
Head and Neck Musculoskeletal Biomechanics
- This project contains models, images and data for analysis of the neck musculoskeletal system. This includes skeletal geometry, muscle anatomy and joint kinematic definitions. | |
Activity Percentile: 55.73 Registered: 2007-10-01 05:53 |
Evertor and invertor muscle co-activation prevents ankle inversion injury
- The study described in this publication used musculoskeletal simulations to compare the capacity of planned invertor/evertor co-activation versus stretch reflexes with physiologic delay to prevent ankle inversion injuries. To achieve this, developed a novel model, muscle stretch controllers, and muscle reflex controllers for simulating landing in OpenSim. By freely providing the models, software plugins defining the controllers, and the resulting simulations, we hope to enable others to answer questions about landing control and injuries using simulations.
All models, data, and simulation results are provided in the downloads area of this project.
For software and sourcecode defining the novel stretch feedback controller and stretch reflex controller, see the related repository on GitHub.
https://github.com/msdemers/opensim-reflex-controllers
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Activity Percentile: 48.85 Registered: 2015-07-20 20:18 |
77 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2> <3> <4>