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ShareScore release 0.7.1
Dataset results
3 results for “sloped walking”
The Effect of a New Generation of Ankle Foot Orthoses on Sloped Walking in Children with Hemiplegia Using the Gait Real Time Analysis Interactive Lab (GRAIL)
<div>The dataset includes the kinematics and kinetics of gait uphill (+10 deg), level ground (0 deg), and downhill (-5 deg) in children with unilateral cerebral palsy who underwent a single session of walking using immersive virtual reality (GRAIL system by Motek), while wearing traditional ankle-foot orthosis (oldAFOs) and a new generation AFO (newCAMOt1).</div> <div>In column A of the file, you will find the patient ID, the type of orthosis used, and the walking condition (e.g., P01_oldAFO_flat0001 indicates that patient 01 performed the walking trial on level ground with the traditional orthosis).</div> <div>In column B of the file, you will find the laterality (R = right, L = left), the name of the analyzed variable, and the stride number (e.g., L_Moment Ankle Flex_step1 means that we are considering the moment at the left ankle of the first left stride).</div> <div>From column C to column CY, you will find the values at the 101 temporal instants of the analyzed variable.</div>
Data and code from: Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing
<p>This repository contains the Julia code, Jupyter notebook, and data used in the study “Healthy young adults use distinct gait strategies to enhance stability when walking on mild slopes and when altering arm swing” by MacDonald et al.</p> <p><strong>Instructions</strong></p> <p>To run this analysis on your computer, both Julia and Jupyter Notebook must be installed. A version of Julia appropriate for your OS can be downloaded from the <a href="https://julialang.org/downloads/">Julia website</a>, and Jupyter can be installed from within Julia (in the REPL) with</p> <pre><code>] add IJulia</code></pre> <p>Alternate instructions for installing Jupyter can be found on the <a href="https://github.com/JuliaLang/IJulia.jl">IJulia github</a> or the <a href="https://jupyter.org/install">Jupyter homepage</a> (not recommended).</p> <p>From within the main repository directory, start Julia and then start Jupyter in the Julia REPL</p> <pre><code>using IJulia notebook(;dir=pwd())</code></pre> <p>or if using a system Jupyter installation, start Jupyter from your favorite available shell (e.g. Powershell on Windows, bash on any *nix variant, etc.). In Jupyter, open the <code>notebooks/analysis.ipynb</code> notebook. Running all cells will reproduce the results for this paper.</p> <p><strong>Description of data</strong></p> <p>The <code>data</code> directory contains all the data used in the production of the results which were statistically tested.</p> <p>Each <code>.mat</code> file contains events and data generated in Visual3D:</p> <ul> <li>Events <ul> <li><code>LTO</code>/<code>RTO</code> (Left/right toe-off)</li> <li><code>LHS</code>/<code>RHS</code> (Left/right heel-strike)</li> <li><code>HIST</code>/<code>HIEN</code> (Hilly start/end)</li> <li><code>ROST</code>/<code>ROEN</code> (Rocky start/end)</li> <li><code>MLST</code>/<code>MLEN</code> (ML translation start/end)</li> </ul> </li> <li>Data <ul> <li><code>LFootPos</code>/<code>RFootPos</code> (Left/right foot COM position)</li> <li><code>TrunkPos/TrunkVel</code>/<code>TrunkAcc</code> (Trunk COM position, velocity, and acceleration)</li> <li><code>HeadPos/HeadVel</code>/<code>HeadAcc</code> (Head COM position, velocity, and acceleration)</li> <li><code>COG</code> (Whole-body COM/COG)</li> </ul> </li> </ul> <p>The <code>.csv</code> files contain system state of the CAREN system produced by D-Flow software, which includes various system and software settings, most pertinent of which is the treadmill speed.</p> <p>The <code>.c3d</code> files contain the raw motion capture data from Vicon Nexus.</p> <ul> </ul> <p>The results of the <code>notebooks/analysis.ipynb</code> notebook are found in the <code>results</code> folder. Please see the paper for a list of the dependent variables and statistical analyses.</p>
Investigation of Walking Training With Different Slope Types in COPD Patients
ClinicalTrials.gov study NCT06283004. IPD Sharing: NO. Countries: 1. Publications: 8.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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)
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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.