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32 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>
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 |
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 |
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 |
Matlab MOtion data elaboration TOolbox for NeuroMusculoSkeletal apps (MOtoNMS)
- MOtoNMS processes experimental data from C3D files of different motion analysis devices and produces input data for OpenSim (.trc and .mot, OpenSim file formats). When available, EMG signals are also processed and can be exported in several formats (.mot, OpenSim motion, .sto, OpenSim Storage, and .txt, plain text format) compatible with the CEINMS toolbox (https://simtk.org/home/ceinms), and easily usable also by other applications.
Procedures implemented in MOtoNMS include: (i) computation of centers of pressure and torques for the most commonly available force platforms (types from 1 to 4, including Bertec, AMTI and Kistler); (ii) rotation of motion capture data between different coordinate systems (those of force platforms, laboratory and OpenSim); (iii) EMG filtering, maximum peak computation, and normalization; (iv) exportation of data ready to be used in OpenSim and CEINMS toolbox. Procedures are highly configurable through user-friendly graphical interfaces that setup XML files listing all the parameters of the execution.
The architecture has been designed to easily accommodate new contributions in instrumentations, protocols, and methodologies. Additionally, data management results in a clear organization of input data and an automatic generation of output directories with a uniquely defined structure.
The tool has been already tested on data from several laboratories with different instruments and procedures for the data collection.
MOtoNMS is released under GNU General Public Licence and freely available to the community without warranty. The software requires either Motion Labs C3D Server software or BTK (Biomechanical ToolKit).
A manual is included with the software, while a html version is always available from the GitHub Project Pages at http://rehabenggroup.github.io/MOtoNMS/. For doubts, suggestions, bugs please either use the MOtoNMS forum or send us an email. This is an ongoing project, any feedback is really appreciated.
When using MOtoNMS or our Test Data, please acknowledge the authors and cite our main publication:
Mantoan et al. Source Code for Biology and Medicine (2015) 10:12
DOI 10.1186/s13029-015-0044-4
http://www.scfbm.org/content/10/1/12 | |
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Activity Percentile: 75.95 Registered: 2014-02-16 11:33 |
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: 72.14 Registered: 2013-02-19 05:59 |
Batch OpenSim Processing Scripts (BOPS)
- BOPS performs batch processing of common OpenSim procedures (Inverse Kinematics - IK, Inverse Dynamics - ID, Muscle Analysis - MA, Static Optimization - SO, and Joint Reaction Analysis - JRA) and stores output, logging information, setup files, and plots in an ordered structure of folders.
We implemented BOPS using OpenSim APIs, that receive the following information through setup files: (i) name and weight of each marker (IK); (ii) external loads (ID); (iii) muscles and moment arms of interest (MA); (iv) static optimization conditions, and muscle actuators loads (SO); (v) joints of interest (JRA). The user is in charge of defining the appropriate configuration for its data, but we already provide several templates for each setup file to speed up their customization.
A MATLAB Graphical User Interface (GUI) is available to simplify the execution of procedures. The use of the GUI is not limited to inputting the setup files. The user can also select: (i) the OpenSim procedures to execute, (ii) the trials to process, (iii) the OpenSim model to use on the simulations, (iv) the cut-off frequencies for the filtering, (v) the residual actuators, (vi) the output variables to plot and the x-axis label.
The software only requires to configure MATLAB for the use of OpenSim API (http://simtk-confluence.stanford.edu:8080/display/OpenSim/Scripting+with+Matlab), and it is based on the data folder organization provided by MOtoNMS software (https://simtk.org/home/motonms).
BOPS stores its outputs in folders that are automatically created and that integrate perfectly in the structure provided by MOtoNMS software (https://simtk.org/home/motonms). We designed the two tools to work in close cooperation to transform the data collected in a motion analysis laboratory into inputs for OpenSim and CEINMS (https://simtk.org/home/ceinms) tools.
BOPS is released under Apache v2.0 License and freely available to the community without warranty. Latest updates can be found on the GitHub repository (https://github.com/RehabEngGroup/BOPS).
Thanks to the recent join of the Human Movement Biomechanics Laboratory (University of Ottawa, Canada) to the project, the tool has been refined and extensively tested on data from several laboratories and with different combinations of procedures, setups and user choices. Their precious contribution has allowed also the addition of the JRA procedure to those already available and led to the release of v2.0, a definitely improved and more stable version.
A tutorial video exemplifying how to use BOPS v2.0 is available in the Documents section.
For any doubts, suggestions, bugs please either use the BOPS forum or send us an email.
This is an ongoing project, therefore any feedback is really appreciated.
When using BOPS or our Test Data, please acknowledge the authors and cite our main publication:
Bruno L. S. Bedo, Alice Mantoan, Danilo S. Catelli, Willian Cruaud, Monica Reggiani & Mario Lamontagne (2021): BOPS: a Matlab toolbox to batch musculoskeletal data processing for OpenSim, Computer Methods in Biomechanics and Biomedical Engineering
DOI: 10.1080/10255842.2020.1867978 | |
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Activity Percentile: 69.08 Registered: 2015-09-05 18:12 |
A three-dimensional musculoskeletal model of the dog
- The domestic dog is interesting to investigate because of their wide range of body size, body mass, and physique. In the last several years, the number of clinical and biomechanical studies on dog locomotion has increased. However, the relationship between body structure and joint load during locomotion, as well as between joint load and degenerative diseases of the locomotor system (e.g. dysplasia), are not sufficiently understood. Collecting this data through in vivo measurements/records of joint forces and loads on deep/small muscles is complex, invasive, and sometimes unethical. The use of detailed musculoskeletal models may help fill the knowledge gap. We describe here the methods we used to create a detailed musculoskeletal model with 84 degrees of freedom and 134 muscles. Our model has three key-features: three-dimensionality, scalability, and modularity. We tested the validity of the model by identifying forelimb muscle synergies of a beagle at walk. We used inverse dynamics and static optimization to estimate muscle activations based on experimental data. We identified three muscle synergy groups by using hierarchical clustering. The activation patterns predicted from the model exhibit good agreement with experimental data for most of the forelimb muscles. We expect that our model will speed up the analysis of how body size, physique, agility, and disease influence neuronal control and joint loading in dog locomotion. | |
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Registered: 2020-11-30 08:11 |
Full Body Model to Perform Deep Squatting and High Hip Flexion Tasks
- This customized musculoskeletal is suitable for analysis with up to 138 degrees of hip flexion and 145 degrees of knee flexion and was based on the previously published model by Rajagopal et al. (2016) and Lai et al. (2017).
Four wrapping surfaces were updated:
Gmax1_at_pelvis
Gmax2_at_pelvis
KnExt_at_fem
KnExtVL_at_fem
Three wrapping surfaces were implemented:
Post_at_pelvis
Gmed_at_pelvis
Flex_at_femhead
To cite this article: Danilo S. Catelli, Mariska Wesseling, Ilse Jonkers & Mario Lamontagne (2019): A musculoskeletal model customized for squatting task, Computer Methods in Biomechanics and Biomedical Engineering, 22(1):21-24.
DOI: 10.1080/10255842.2018.1523396
Link to this article: https://doi.org/10.1080/10255842.2018.1523396 | |
Registered: 2017-11-08 18:33 |
Tim's OpenSim Utilities
- This project site is concerned with extending the functionality of OpenSim through the use of scripting tools and plugins.
Click on the downloads link to browse the set of freely available OpenSim tools for download.
*******************************************************
Previously delivered interactive webinars demonstrating
the use of the Pseudo-Inverse Induced Acceleration
plugin for OpenSim (IndAccPI).
http://www.stanford.edu/group/opensim/support/webinars.html
******************************************************* | |
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Registered: 2009-09-01 00:52 |
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 |
Studying Anterior Cruciate Ligament Strains in Young Female Athletes
- The central goal of this study is to contribute toward advancements made in determining the underlying causes of anterior cruciate ligament (ACL) injuries in young female athletes performing high impact activities like stop jumps. ACL injuries are frequently incurred by recreational and professional young female athletes during non-contact impact activities in sports like volleyball and basketball. This musculoskeletal-neuromuscular study investigated stop jumps and factors related to ACL injury like knee valgus and internal–external rotations and moment loads, as well as ACL strains and internal forces. The dynamic simulation steps undertaken for this analysis using OpenSim 3.2 include Model Scaling, Inverse Kinematics, Residual Reduction, Computed Muscle Control and Forward Dynamics. | |
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Activity Percentile: 56.49 Registered: 2014-08-05 18:24 |
Marker registration method informed by anatomical reference frame orientations
- Accurate computation of joint angles from optical marker data using inverse kinematics methods requires that the locations of markers on a model match the locations of experimental markers on participants. Marker registration is the process of positioning the model markers so that they match the locations of the experimental markers. Markers are typically registered using a graphical user interface (GUI), but this method is subjective and may introduce errors and uncertainty to the calculated joint angles and moments. In this investigation, we use OpenSim to isolate and quantify marker registration–based error from other sources of error by analyzing the gait of a bipedal humanoid robot for which segment geometry, mass properties, and joint angles are known. We then propose a marker registration method that is informed by the orientation of anatomical reference frames derived from surface-mounted optical markers as an alternative to user registration using a GUI. The proposed orientation registration method reduced errors in joint angles and moments compared to the user registration method, and eliminated variability among users. Our results show that a systematic method for marker registration that reduces subjective user input can make marker registration more accurate and repeatable. | |
Registered: 2021-01-18 04:28 |
A predictive model of muscle excitations based on muscle modularity
- Humans can efficiently walk across a large variety of terrains and locomotion conditions with little or no mental effort. It has been hypothesized that the nervous system simplifies neuromuscular control by using muscle synergies, thus organizing multi-muscle activity into a small number of coordinative co-activation modules. With this project we want to investigate how muscle modularity is structured across a large repertoire of locomotion conditions including five different speeds and five different ground elevations. For this we have used the non-negative matrix factorization technique in order to explain EMG experimental data with a low-dimensional set of four motor components. This descriptive analysis was translated into a predictive model that could: 1) Estimate how motor components modulate across locomotion speeds and ground elevations. This implies not only estimating the non-negative factors temporal characteristics, but also the associated muscle weighting variations. 2) Estimate how the resulting muscle excitations modulate across novel locomotion conditions and subjects. | |
Activity Percentile: 38.17 Registered: 2015-08-12 06:11 |
C3D Extraction Toolbox
- This toolbox is of benefit to musculoskeletal modellers in the field of biomechanics / bioengineering to assist extracting kinematic, kinetic, and EMG information directly from a C3D file for Matlab manipulation or for input to OpenSim biosimulation software. The scripts can be configured for any laboratory configuration. This software is free without warranty but I do ask for acknowledgement if used in publications. Free download is available with documentation and two examples included.
Main features of this script include:
Custom markerset extraction
Foot-plate detection algorithm
Kinetic extraction (ground reaction forces / moments)
Center of pressure calculation
Transformation to customizable model coordinate system
Custom EMG acquisition & processing tools
XML file production (for OpenSim)
Lab customizable
The scripts require Motion Labs C3D Server software (freeware) and XML Toolbox (Marc Molinari)(freeware) which is included with the script download. Also requires Matlab 2008 or greater (32 bit only) with the Signal Processing Toolbox.
Additional C3D software may be useful and these are available at http://www.c3d.org/c3dapps.html. Review the included manual for version updates and additions. Please inform me of bugs / suggestions to improve as this will be an ongoing project. | |
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Registered: 2008-10-03 01:17 |
UW Simulation Tools
- This project contains a collection of tools developed at UW-Madison for musculoskeletal modeling in OpenSim. These tools have been developed such that they can be plugged into current OpenSim models. | |
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Activity Percentile: 17.56 Registered: 2015-04-08 22:37 |
Modeling kinematic and dynamic redundancy
- The coordination of the human musculoskeletal system is deeply influenced by its redundant structure, in both kinematic and dynamic terms. Noticing a lack of a relevant, thorough treatment in the literature, we formally address the issue in order to understand and quantify factors affecting the motor coordination. We employed well-established techniques from linear algebra and projection operators to extend the underlying kinematic and dynamic relations by modeling the redundancy effects in null space. We distinguish three types of operational spaces, namely task, joint and muscle space, which are directly associated with the physiological factors of the system. A method for consistently quantifying the redundancy on multiple levels in the entire space of feasible solutions is also presented. We evaluate the proposed muscle space projection on segmental level reflexes and the computation of the feasible muscle forces for arbitrary movements. The former proves to be a convenient representation for interfacing with segmental level models or implementing controllers for tendon driven robots, while the latter enables the identification of force variability and correlations between muscle groups, attributed to the system’s redundancy. Furthermore, the usefulness of the proposed framework is demonstrated in the context of estimating the bounds of the joint reaction loads, where we show that misinterpretation of the results is possible if the null space forces are ignored. This work presents a theoretical analysis of the redundancy problem, facilitating application in a broad range of fields related to motor coordination, as it provides the groundwork for null space characterization. The proposed framework rigorously accounts for the effects of kinematic and dynamic redundancy, incorporating it directly into the underlying equations using the notion of null space projection, leading to a complete description of the system.
https://github.com/mitkof6/musculoskeletal-redundancy
https://github.com/mitkof6/feasible_muscle_force_analysis | |
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Registered: 2018-05-17 10:19 |
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 |
Clinical Gait Analysis (Vicon - OpenSim) Toolbox
- We present a semi-automatic scaling approach to generate personalized musculoskeletal models of children with gait impairment using a marker registration method informed by the static pose of the conventional gait model. The final scaled model adopts the same rotational degrees of freedom of the conventional gait model, thus allowing consistency in kinematic output between the two models. | |
Activity Percentile: 0.00 Registered: 2015-03-23 19:02 |
32 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>