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25 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>
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 |
Are subject-specific musculoskeletal models robust to parameter identification?
- This study analyzed the sensitivity of the predictions of an MRI-based musculoskeletal model (i.e., joint angles, joint moments, muscle and joint contact forces) during walking to the unavoidable uncertainties in parameter identification, i.e., body landmark positions, maximum muscle tension and musculotendon geometry. To this aim, we created an MRI-based musculoskeletal model of the lower limbs, defined as a 7-segment, 10-degree-of-freedom articulated linkage, actuated by 84 musculotendon units. We then performed a Monte-Carlo probabilistic analysis perturbing model parameters according to their uncertainty, and solving a typical inverse dynamics and static optimization problem using 500 models that included the different sets of perturbed variable values. Model creation and gait simulations were performed by using freely available software that we developed to standardize the process of model creation, integrate with OpenSim and create probabilistic simulations of movement. | |
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Activity Percentile: 92.37 Registered: 2014-11-10 15:19 |
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 |
Reference Models for Multi-Layer Tissue Structures
- This project aims to establish the founding knowledge, data and models for the mechanics of multi-layer tissue structures of the limbs, particularly of the lower and upper legs and arms. The activity is targeted to promote scientific research in layered tissue structures and allow reliable virtual surgery simulations for clinical training and certification.
This research and development project titled “Reference Models for Multi-Layer Tissue Structures" was conducted by the Cleveland Clinic Foundation and was made possible by a contract vehicle which was awarded and administered by the U.S. Army Medical Research & Materiel Command under award number: W81XWH-15-1-0232. The views, opinions and/or findings contained in this website are those of the authors and do not necessarily reflect the views of the Department of Defense and should not be construed as an official DoD/Army position, policy or decision unless so designated by other documentation. No official endorsement should be made. | |
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Registered: 2015-08-24 12:54 |
Musculoskeletal Representation of Large Repertoires of Hand Grasping in Primates
- The project aims to investigate and characterize the complex function of the primate hand at the musculoskeletal level. The OpenSim models used in this project enabled extracting joint angles from 27 degrees of freedom as well as length of 50 musculotendon units in the hand and upper extremity. Results demonstrated both a more compact representation and a higher decoding capacity of grasping tasks when movements were expressed in the muscle kinematics domain than when expressed in the joint kinematics domain. The OpenSim models in the project were adapted from the upper extremity model by Holzbaur et al., Ann.Biomed. Eng., 2005. | |
Activity Percentile: 67.56 Registered: 2015-02-10 15:59 |
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 |
HiTRACE: High-Throughput Robust Analysis for Capillary Electrophoresis
- This project contains the HiTRACE software that allows users to accurately and automatically perform key quantitative analysis tasks involved in high-throughput capillary electrophoresis (CE) of nucleic acids. CE has become a workhorse technology underlying high-throughput experimental methods such as high-speed genome sequencing and large-scale footprinting for nucleic acid structural inference. Despite the wide availability of CE-based equipment, there remain challenges in leveraging the full power of CE for quantitative analysis of RNA and DNA structure. We developed HiTRACE in order to address this issue. See <a href="http://arxiv.org/abs/1104.4337">Preprint</a> for more information. | |
Activity Percentile: 53.82 Registered: 2010-11-10 08:11 |
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 |
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 |
Allosteric Transitions of Supramolecular Systems Explored by Network Models
- Most proteins are biomolecular machines. They perform their function by undergoing changes between different structures. Understanding the mechanism of transition between these structures is of major importance to design methods for controlling such transitions, and thereby modulating protein function.
However, exploring the transition between conformations is difficult, both experimentally and computationally, due to the transient nature of the intermediate, high energy conformers crossed over as the molecule undergoes structural changes. In many cases, only the two ending structures are known from experiments. Furthermore, the passage between the two end points does not necessarily involve a single pathway, but multiple pathways in the multidimensional energy landscape associated with the macromolecular structures. To bridge between structure and function, a molecular understanding of the most probable transition pathways between the two end structures is required.
While there are many computational methods for exploring the transitions of small proteins, the task of exploring the transition pathways becomes prohibitively expensive in the case of supramolecular systems. Coarse-grained models that lend themselves to analytical solutions appear to be the only possible means of approaching such cases. Motivated by the utility of elastic network models for describing the collective dynamics of biomolecular systems, and by the growing theoretical and experimental evidence in support of the intrinsic accessibility of functional substates, we introduce a new method, adaptive anisotropic network model (aANM) for exploring functional transitions.
As described by aANM, a series of intermediate conformations along the transition pathways between the initial and final conformations were generated by successive deformations of both end structures that were iteratively updated. The directions of deformations were determined by implementing the deformations along the directions of dominant ANM modes accessible to the intermediate states. The recruitment of the particular subsets of modes results from a tradeoff between minimizing the path length and selecting the direction of the lowest increase in internal energy. To calculate the ANM modes, please visit our related websites.
ANM: http://ignmtest.ccbb.pitt.edu/cgi-bin/anm/anm1.cgi
GNM: http://ignm.ccbb.pitt.edu/GNM_Online_Calculation.htm
PCA_NEST: http://ignm.ccbb.pitt.edu/oPCA_Online.htm
The bacterial chaperonin GroEL is a supramolecular machine that has been broadly studied in recent years using both experimental and theoretical or computational methods. Yet, a structure-based analysis of the transition of the intact chaperonin between its functional forms has been held back by the large size of the chaperonin. The aANM method is proposed as a first approximation toward approaching this challenging task.
The application of aANM to GroEL, not only elucidated the highly probable pathways and the hierarchic contribution of modes to achieve the transition; but also provided us with biologically significant information on critical interactions and sequence of events occurring during the chaperonin machinery and key contacts that make and break at the transition.
On a practical side, the major utility of the method lies in its application to the transitions of supramolecular systems beyond the range of exploration of other computational methods. The computing time in the present method is several orders of magnitude shorter than that required in regular molecular dynamics or Brownian dynamics simulations.
*Figure above: Snapshots of the protein chaperonin GroEL in its transition pathway, evolving from open (upper left) to closed form (lower right). The color scheme was inspired by Wassily Kandinsky and his artwork “Squares and Concentric Rings”.
For more information, please visit:
http://www.ccbb.pitt.edu/Faculty/bahar/index.php
http://www.ccbb.pitt.edu/Faculty/bahar/publications/YZResearch/Coupling.html
http://www.ccbb.pitt.edu/Faculty/bahar/publications/YZResearch/Transitions.html | |
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Activity Percentile: 0.00 Registered: 2010-06-22 01:53 |
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 |
SCIentific analysis of molecular EXperiments
- This is a collection of advanced analysis tools for molecular experiments. Currently we offer the following features:
- calculation of dynamical fingerprints | |
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Activity Percentile: 0.00 Registered: 2011-02-03 17:31 |
Running in the wild: energetics explain ecological running speeds
- Human runners have long been thought to have the ability to consume a near constant amount of energy per distance traveled regardless of speed, allowing speed to be adapted to particular task demands with minimal energetic consequence. However, recent and more precise laboratory measures indicate that humans may in fact have an energy-optimal running speed. Here we characterize runners’ speeds in a free-living environment and determine if preferred speed is consistent with task or energy dependent objectives.
We analyzed data from anonymized runners using the Lumo Run wearable device (Lumo Bodytech Inc.), in combination with pooled laboratory data of running energetics [1,2,3], to answer two questions. First, do runners adapt their preferred speed for different distance tasks? If minimizing cost of transport is not a dominant objective, and runners instead tailor their preferred speed to the task (for example minimizing time across run distance), we might expect faster paces for shorter distances and slower paces for longer distances. Second, are runners’ preferred speeds energy optimal? If minimizing cost of transport is a dominant objective, we expect preferred running speeds to be unaffected by the task (run distance) and also consistent with speeds that minimize cost of transport.
We found that individual runners preferred a particular speed that did not change across commonly run distances. We compared data from lab experiments that measured participants’ energy-optimal running speeds to the free-living preferred speeds of age- and gender-matched runners in our dataset and found the speeds to be indistinguishable. Human runners prefer a particular running speed that is independent of task distance, and consistent with the objective of minimizing energy expenditure.
[1] Steudel-Numbers KL, Wall-Scheffler CM. Optimal running speed and the evolution of hominin hunting strategies. Journal of Human Evolution 2009;56:355–60.
doi:10.1016/j.jhevol.2008.11.002.
[2] Rathkey JK, Wall-Scheffler CM. People choose to run at their optimal speed. Am J Phys Anthropol 2017:1–9.
doi:10.1002/ajpa.23187.
[3] Willcockson MA, Wall-Scheffler CM. Reconsidering the effects of respiratory constraints on the optimal running speed. Med Sci Sports Exerc 2012;44:1344–50. doi:10.1249/MSS.0b013e318248d907.
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Registered: 2022-03-13 13:08 |
Tibial forces in independently ambulatory children with spina bifida
- Experimental motion capture and bone strength data and simulation results from 16 independently ambulatory children with spina bifida and 16 age- and sex-matched children with typical development. Additional motion capture and EMG data and simulation results for 6 independently ambulatory children with spina bifida and 1 child with typical development. Custom scripts were used to calculate joint kinematics, moments, and forces. Post-simulation analyses were conducted to compare these waveforms between the group with spina bifida and the group with typical development.
The manuscript using these data and simulations can be found here:
Lee MR, Hicks JL, Wren TAL, and Delp SL (2022). Independently ambulatory children with spina bifida experience near-typical knee and ankle joint moments and forces during walking. Gait and Posture, 99:1-8. https://doi.org/10.1016/j.gaitpost.2022.10.010 | |
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Registered: 2022-06-01 20:00 |
Acetaminophen Induced Liver Injury
- The AILI project is a type of In-Silico Liver (ISL) project, which consists of a body of Java code used and reused for exploring hypothetical liver mechanisms. For AILI, the liver mechanisms are those that cause cellular damage, specifically necrosis, because of exposure to acetaminophen. Moreover, the model, a mouse analog, is used for virtual experimentation to explore and explain AILI phenomena, analogous to wet-lab experimentation. A recent addition to this project is studying the disconnect between in vitro and in vivo wet-lab experiments by comparing and contrasting virtual Mouse and Culture Analogs. | |
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Activity Percentile: 0.00 Registered: 2015-05-07 23:25 |
Multiscale Modeling of the Mammalian Circadian Clock: The Role of GABA Signaling
- The synchronization and entrainment of coupled biological oscillators is an emerging research area in complex network systems. The mammalian circadian clock located in the suprachiasmatic nucleus (SCN) of the hypothalamus consists of approximately 20,000 pacemaker neurons that are coupled together to produce a robust overall rhythm that drives other bodily functions such as sleep patterns. The SCN represents an ideal model system for studying biological network design and behavior due to accumulating data on individual SCN neurons and their interactions. Experimental studies have shown that SCN intercellular communication is primarily mediated by two neurotransmitters: vasoactive intestinal peptide (VIP) and gamma-aminobutyric acid (GABA). While VIP is well established as an essential synchronizing agent, the role of GABA with respect to its inhibitory/excitatory, day/night, synchronizing and entrainment effects remains controversial. Improved understanding of neurotransmitter mediated intercellular signaling in the SCN will have important clinical implications for prevention and treatment of circadian rhythm disruptions, including mood and sleep disorders and metabolic diseases.
The goal of this project is to develop a multiscale model of the SCN and to integrate this model with targeted experiments and novel computational tools to gain improved understanding of SCN connectivity, synchronization and entrainment properties. The research focuses on GABA signaling because its role in the SCN is prominent, not well understood, and recent advances by the three participating investigators will enable a complete and careful dissection of the role of this common neurotransmitter with synapse-level resolution across large arrays of circadian neurons. The multiscale model will establish a link between core clock genes and ion channels at the individual cell level and network synchronization and entrainment behavior at the SCN tissue level through cell-to-cell connectivity. Targeted experiments will be performed to inform the construction and validate the predictions of the network model. General computational techniques for model reduction and efficient simulation of heterogeneous cellular networks will be developed to facilitate analysis of model behavior over a wide range of environmental conditions. The research has the potential to be highly transformative by both advancing the multiscale modeling of coupled oscillators/complex networks and by fundamentally changing our understanding of GABA signaling in circadian timekeeping and potentially in other brain regions. | |
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Registered: 2017-03-28 00:27 |
Capacitive Sensing for Natural Environment Biomechanics Monitoring
- Link to Code: https://github.com/opearl-cmu/CapacitiveSensingKinematics
The included codebase illustrates how to use capacitive sensing data within two different
wearable kinematics algorithms, CSInverseKinematics and CSOptimalControl. It shows how to load raw CS signals, process them, analyze them, learn from them, and predict kinematics with them on their own or in combination with other wearables.
Link to Dataset: https://github.com/opearl-cmu/CapacitiveSensingDataset
The following dataset comprises data from two experiments. The first dataset includes time-synchronized measurements of (1) muscle bulging acquired via a wearble lower limb capacitive sensing sleeve at the shank, (2) neural excitation measurements from electromyography, and (3) inferred muscle moments from static optimization performed in OpenSim with optical motion capture and instrumented treadmill data. 20 participants were recorded walking normally and with a 5-degree toe-in foot progression angle, a therapeutic modification used to mitigate progression of knee osteoarthritis. Measurements for CS and EMG were taken both inside a traditional motion capture laboratory environment and outside in natural environments.
The second dataset includes measurements of (1) muscle bulging acquired via wearable lower limb capacitive sensing sleeves located at both the shank and thigh of both legs, (2) neural excitation measurements from electromyography, (3) optical motion capture and instrumented treadmill data, (4) XSens inertial measurement unit data, and (5) magnetic resonance imaging (MRI) body composition scan results. 10 healthy participants were recorded walking normally and with a mock impaired stiff-knee gait, along with 1 total knee arthroplasty patient. Measurements for CS, IMUs, and mocap were taking simultaneously, as well as measurements of EMG, IMUs, and mocap inside of the lab on an instrumented treadmill. The provided dataset enables the comparison of CS data with any biomarker in a consistent OpenSim/MATLAB ready formatting.
Please cite the following when using this code or data:
Owen Pearl, Nataliya Rokhmanova, Louis Dankovich, Summer Faille, Sarah Bergbreiter, Eni Halilaj. (2022) Capacitive Sensing for Natural Environment Rehabilitation Monitoring, Nature (under review). https://doi.org/10.21203/rs.3.rs-1902381/v. | |
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Registered: 2022-06-15 22:25 |
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 |
25 projects in result set. Displaying 20 per page. Projects sorted by alphabetical order.
<1> <2>