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48 results for “Motion Modelling”
Forearm pro-supination motion videos, 3D models, and simulation scenes
<p>This dataset contains 3D models for a patient-specific forearm bones (radius and ulna) with its interosseous membrane (IOM) ligament it composed of several heterogeneous parts, comprising the central band (CB), accessory band (AB), distal oblique accessory cord (DOAC), distal oblique bundle (DOB), and proximal oblique cord (POC).</p> <p>- simulation_scenes_iom_multi_different_res.zip</p> <p>contains the models with the simulation scenes written in SOFA framework. The IOM is modeled as 7 components. Different resolutions have been experimented.</p> <p>- simulation_scenes_iom_single_cbp.zip</p> <p>contains the models with the simulation scenes written in SOFA framework. The IOM is modeled as a single wide band ligament. Different resolutions have been experimented.</p> <p>- prosup_simulation_videos.zip</p> <p>A folder containing videos of the simulations.</p> <p>- Prosup_Tech_report</p> <p>A technical report describing the approach of the numerical simulations</p>
Data for publication: Autoadaptive motion modelling for MR-based respiratory motion estimation
<p>This repository contains four T1-weighted 2D MR slice datasets from multiple slice positions covering the entire thorax during free breathing and breath holds. The data was used to evaluate our novel autoadaptive respiratory motion model which we proposed in [1]. In particular, the datasets contain the following:</p> <ol> <li>Acquisition of all sagittal slice positions covering the thorax and one coronal slice position acquired during a breath hold.</li> <li>Results of registration between adjacent sagittal slice positions [control point displacements (cpp) and displacement fields (dfs)]</li> <li>40 dynamic acquisitions of each slice position also present in the breath-hold acquired during free breathing. </li> <li>Results of registration of the dynamic acquisitions to the respective breath-holds slices (cpp's and dfs's). </li> </ol> <p>The data is divided into 4 zip files, each containing the data of one volunteer. The folder structure for each is as follows:</p> <blockquote> <p>|-- bhs (breath hold data)<br /> | |-- images (images)<br /> | | |-- cor<br /> | | `-- sag<br /> | `-- mfs_slpos2slpos (registration results)<br /> | `-- sag<br /> `-- dyn (dynamic free-breathing data)<br /> |-- images (images)<br /> | |-- cor<br /> | `-- sag<br /> `-- mfs_tpos2tpos (registration results)<br /> |-- cor<br /> `-- sag</p> </blockquote> <p>Please, see our publication [1] for details on the acquisition sequence and registration used. </p> <p>--</p> <p>[1]: CF Baumgartner, C Kolbitsch, JR McClelland, D Rueckert, AP King, <em>Autoadaptive motion modelling for MR-based respiratory motion estimation</em>, Medical Image Analysis (2016), http://dx.doi.org/10.1016/j.media.2016.06.005</p>
Reprocessing of Three-Decade GNSS Observations: Millimeter-Level Global Velocity Field and Plate Motion Model Refinement
<p>The accurate and reliable Terrestrial Reference Frame (TRF) functions as a unified spatiotemporal datum crucial for solid earth research, encompassing disciplines such as geodesy and geodynamics. High-precision GNSS velocity field products stand out as pivotal foundational data for the maintenance of the TRF. This dataset encapsulates the outcomes of two GNSS velocity field refinement products: Global GNSS Velocity Model 2020 (GGVM2020) and the Global Interpolation Velocity Model 2020 (GIVM2020). GGVM2020 comprises velocity values and formal errors derived from over 3000 GNSS sites worldwide. And GIVM2020 incorporates speed values from approximately 2000 grid points on land globally, with a grid spacing of 3 degrees.</p>
A Clustering Approach to Improve IntraVoxel Incoherent Motion Maps from DW-MRI using Conditional Auto-Regressive Bayesian Model
<p>Simulated data generated and used in the paper "A Clustering Approach to Improve IntraVoxel Incoherent Motion Maps from DW-MRI using Conditional Auto-Regressive Bayesian Model" are here available.</p> <p>Results generated from both simulated and clinical datasets are also available on the excel tables.</p>
Supplementary dataset for " Kinematic rupture modeling of broadband ground motion from the 2022 MS6.9 Menyuan earthquake"
<p>This is the data used in " Kinematic rupture modeling of broadband ground motion from the 2022 MS6.9 Menyuan earthquake". The paper is currently under review.</p>
Dataset for High-resolution mantle flow models reveal importance of plate boundary geometry and slab pull forces on generating tectonic plate motions
<p>This repository contains the plugin and dataset used to setup models in the manuscript: "High-resolution mantle flow models reveal importance of plate boundary geometry and slab pull forces on generating tectonic plate motions".</p> <p>The material model plugin used in our models is in the "plugins" folder. The "models" folder contains the reference input parameter file described in the paper. All other model configurations shown in the paper can be obtained by modifying this parameter file. The input files used to set up the models are in the respective folder. Additionally, the Jupyter notebook used to compute residuals of our models is provided in the "scripts" folder.</p> <p> </p>
Attenuation of Seismic Waves and Ground Motion Model of the Reykjanes Peninsula, Iceland
<p>Events.csv - Location of used events</p> <p>Amplit_A_HOR.csv, Amplit_A_VER.csv - Acceleration amplitudes (Horizonlat/Vertical) and parameters of inversion</p> <p>Amplit_V_HOR.csv, Amplit_V_VER.csv - Velocity amplitudes (Horizonlat/Vertical) and parameters of inversion</p> <p>Amplit_D_HOR.csv, Amplit_D_VER.csv - Displacement amplitudes (Horizonlat/Vertical) and parameters for inversion</p> <p><br><br></p> <p> </p>
Three dimensional localization refinement and motion model parameter estimation for confined single particle tracking under low-light conditions: Simulation datasets
<p><span>The datasets store both motion and observation information of a single fluorescent sub-diffraction limit-sized particle moving in a three-dimensional confined environment. The confined motion is following a nonlinear model driven by non-Gaussian noise, the observation is formed by engineered Double-helix (DH) point spread function (PSF) and captured by scientific complementary metal-oxide semiconductor (sCMOS) camera. Based on our prior computationally efficient application of Sequential Monte Carlo - Expectation Maximization (SMC-EM), we extended it to handle the DH-PSF for encoding the three-dimensional position of the particle in two-dimensional image plane of the camera. We focus on studying the datasets at low signal and low signal-to-background ratio (SBR). Based on the datasets across different SBR and confinement lengths, a quantitative comparison is conducted to show that in the low signal regime, the SMC-EM approach outperforms the other methods while at higher signal-to-background levels, SMC-EM and the MLE-based methods perform equally well and both are significantly better than fitting to the MSD. In addition, our results indicate that at smaller confinement lengths where the nonlinearities dominate the motion model, the SMC-EM approach is superior to the alternative approaches. </span></p>
CARRT - Motion Capture Data for Robotic Human Upper Body Model
<p>As advancements in the study of human activity have progressed in recent years, researchers have directed their attention towards analyzing human daily activities to investigate a diverse range of performance metrics unconsciously optimized by individuals while engaged in specific tasks. To replicate these movements in robotic systems based on human models, researchers have developed a framework for robot motion planning capable of utilizing various optimization methods to reproduce such motions through human demonstrations. In this process, capturing the movements of the human body and the objects involved in the demonstrations is imperative, as they provide essential information for the motion planning procedure. The objective of this dataset is to present human motion data while performing activities of daily living. This dataset encompasses comprehensive and precise whole-body motion data of individuals collected using a Vicon motion capture system, which facilitated the development of a full-body model integrated into OpenSim and MATLAB. The dataset comprises nine different daily living activities and eight Range of Motion activities performed by ten healthy participants. A publicly accessible whole-body human motion database has been established, encompassing raw motion data in .c3d format, motion data in .csv format for the OpenSim model, and post-processed motion data for the MATLAB model.</p>
Ground motions for the Greater Wellington Region from selected synthetic earthquakes, modelled using OpenQuake
<p>Model results and plots forming an electronic supplement to the GNS Science Report: </p> <p>Howell A, Penney C, Kaiser AE, Fry B. 2023. Modelling ground motions in the Greater Wellington region from multi-fault earthquakes in central Aotearoa New Zealand. Lower Hutt (NZ): GNS Science. 19 p. (GNS Science report; 2023/45). https://doi.org/10.21420/Z9SM-0G27 . </p> <p>The folder includes:</p> <ul> <li>A CSV file containing summary information for each of the 20 modelled earthquakes.</li> <li>Plots of the slip distribution of each event.</li> <li>Plots of shaking (PGA, Sa(0.5) and (Sa(1.5) for each event).</li> <li>GeoTIFFs representing the crustal and subduction components of ground motions for each earthquake.</li> </ul> <p>Please read the report for details of the modelling and limitations of the approach.</p> <p> </p> <p> </p>
Three dimensional localization refinement and motion model parameter estimation for confined single particle tracking under low-light conditions: Simulation datasets
Open the record for dataset details and reuse information.
Upper body biomechanical model for the analysis of the wrist motion amplitude
<p>The following files are available:</p> <p>- The Visual3D files (.cmo) corresponding to the upper body biomechanical model</p> <p>- Videos of a pilot data acquisition from a healthy individual</p> <p>- Videos of the biomechanical models of 11 individuals with Parkinson's disease, used to assess the motion amplitude of the wrist with and without the use of an active orthosis, for four scenarios: Extension Without Orthosis (ENO), Extension With Orthosis (EWO), Flexion Without Orthosis (FNO) and Flexion With Orthosis (FWO)</p>
Data from: Seeds in motion: genetic assignment and hydrodynamic models demonstrate concordant patterns of seagrass dispersal
Movement is fundamental to the ecology and evolutionary dynamics within species. Understanding movement through seed dispersal in the marine environment can be difficult due to the high spatial and temporal variability of ocean currents. We employed a mutually enriching approach of population genetic assignment procedures and dispersal predictions from a hydrodynamic model to overcome this difficulty and quantify the movement of dispersing floating fruit of the temperate seagrass Posidonia australis Hook.f. across coastal waters in southwestern Australia. Dispersing fruit cohorts were collected from the water surface over two consecutive years and seeds were genotyped using microsatellite DNA markers. Likelihood-based genetic assignment tests were used to infer the meadow of origin for seed cohorts and individuals. A three-dimensional hydrodynamic model was coupled with a particle transport model to simulate the movement of fruit at the water surface. Floating fruit cohorts were mainly assigned genetically to the nearest meadow, but significant genetic differentiation between cohort and most-likely meadow of origin suggested a mixed origin. This was confirmed by genetic assignment of individual seeds from the same cohort to multiple meadows. The hydrodynamic model predicted 60% of fruit dispersed within 20 km, but that fruit were physically capable of dispersing beyond the study region. Concordance between these two independent measures of dispersal provide insight into the role of physical transport for long distance dispersal (LDD) of fruit and the consequences for spatial genetic structuring of seagrass meadows.
Validation of Peak Ground Velocities Recorded on Very-high rate GNSS Against NGA-West2 Ground Motion Models: Dataset
<p>Contains all the data files for the manuscript of the same name.</p>
Intravoxel incoherent motion model of diffusion weighted imaging and diffusion kurtosis imaging in differentiating of local colorectal cancer recurrence from scar/fibrosis tissue by multivariate logistic regression analysis
<p>We uploaded mean of diffusion coefficient (MD) and mean of diffusional Kurtosis values of 56 patients related to the manuscript: Fusco, Roberta, Vincenza Granata, Mario Sansone, Robert Grimm, Paolo Delrio, Daniela Rega, Fabiana Tatangelo, Antonio Avallone, Nicola Raiano, Giuseppe Totaro, Vincenzo Cerciello, Biagio Pecori, and Antonella Petrillo. 2020. "Intravoxel Incoherent Motion Model of Diffusion Weighted Imaging and Diffusion Kurtosis Imaging in Differentiating of Local Colorectal Cancer Recurrence from Scar/Fibrosis Tissue by Multivariate Logistic Regression Analysis" Applied Sciences 10, no. 23: 8609. https://doi.org/10.3390/app10238609</p>
Data for: Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction (Part 2/2)
<p>Magnetic Resonance Imaging measurement data used in our paper about "Free-Breathing Myocardial T1 Mapping using Inversion-Recovery Radial FLASH and Motion-Resolved Model-Based Reconstruction". The data is provided in a file format used by the BART toolbox (DOI: <a href="http://doi.org/10.5281/zenodo.592960">10.5281/zenodo.592960</a>)</p>
Estimating Jaw, Neck, and Shoulder Range of Motion Using an AI Model
ClinicalTrials.gov study NCT06629038. IPD Sharing: NO. Countries: 1. Publications: 14.
Data from: Motion analysis of non-model organisms using a hierarchical model: influence of setup enclosure dimensions on gait parameters of Swinhoe’s striped squirrels as a test case
Open the record for dataset details and reuse information.
Data from: Seeds in motion: genetic assignment and hydrodynamic models demonstrate concordant patterns of seagrass dispersal
Open the record for dataset details and reuse information.
Reproducibility material for ground motion validation of hybrid models
<p>Code and data repository to reproduce research on the effect of model hybridization on ground motion prediction.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.