Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
31
datasets available to search
ShareScore release 0.9.0
Dataset results
31 results for “Prosthesis control”
SYNTHETIC dataset attached to the paper "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis"
<p>SYNTHETIC dataset to replicate the results in "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis", accepted to IEEE/RSJ IROS 2022.</p> <p>In order to fully reproduce the experiments, download also the REAL dataset. </p> <p>To automatically download the REAL and SYNTHETIC dataset, run the script provided at the link below.</p> <p>Code to replicate the results available at: https://github.com/hsp-iit/prosthetic-grasping-experiments</p>
REAL dataset attached to the paper "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis"
<p>REAL dataset to replicate the results in "Grasp Pre-shape Selection by Synthetic Training: Eye-in-hand Shared Control on the Hannes Prosthesis", accepted to IEEE/RSJ IROS 2022.</p> <p>In order to fully reproduce the experiments, download also the SYNTHETIC dataset. </p> <p>To automatically download the REAL and SYNTHETIC dataset, run the script provided at the link below.</p> <p>Code to replicate the results available at: https://github.com/hsp-iit/prosthetic-grasping-experiments</p>
Data from: A multifaceted suite of metrics for comparative myoelectric prosthesis controller research
Open the record for dataset details and reuse information.
Myoelectric prosthesis control using recurrent convolutional neural network regression mitigates the limb position effect
Open the record for dataset details and reuse information.
Data from: The effects of ground-irregularity-cancelling prosthesis control on balance over uneven surfaces
<p>Over half of individuals with a lower-limb amputation are unable to walk on uneven terrain. Using a prosthesis emulator system, we developed an irregularity-cancelling controller intended to reduce the effect of disturbances resulting from uneven surfaces. This controller functions by changing the neutral angles of two forefoot digits in response to local terrain heights. To isolate the effects of the controller, we also programmed a spring-like controller that maintained fixed neutral angles. Five participants with transtibial amputation walked on a treadmill with an uneven walking surface. Compared to the spring-like controller, the irregularity-cancelling controller reduced ankle torque variability by 41% in the sagittal plane and 64% in the frontal plane. However, user outcomes associated with balance were mostly unaffected; only trunk movement variability was reduced, whereas metabolic rate, mediolateral center of mass motion, and variabilities in step width, step length, and step time were unchanged. We conclude that reducing ankle torque variability of the affected limb is not sufficient for reducing the overall effect of disturbances due to uneven terrain. It is possible that other factors, such as changes in step height or disturbances to the intact limb, play a larger role in difficulty balancing while walking over uneven surfaces.</p>
Data and code for intuitive movement-based prosthesis control in virtual reality
<p>This repository contains data and code for</p> <p><strong>Intuitive movement-based prosthesis control enables arm amputees to reach naturally in virtual reality</strong></p> <p>Effie Segas<sup>1</sup>, Sébastien Mick<sup>1,2</sup>, Vincent Leconte<sup>1</sup>, Rémi Klotz<sup>3</sup>, Daniel Cattaert<sup>1</sup>, Aymar de Rugy<sup>1</sup></p> <p><sup>1</sup> Univ. Bordeaux, CNRS, INCIA, UMR 5287, F-33000 Bordeaux, France</p> <p><sup>2</sup> ISIR UMR 7222, Sorbonne Université, CNRS, Inserm, F-75005, France</p> <p><sup>3</sup> CMPR Tour de Gassies, F-33520 Bruges, France</p> <p> </p> <p> </p> <p>It contains a dataset <strong>(DataOnline_2022_SPCA21 folder</strong>) of three experiments of able-bodied participants (<strong>Exp1 and Exp2 folders</strong>) and amputee participants (<strong>Exp3 folder</strong>) performing a pick-and-placed task in a virtual reality environment with or without movements-based Artificial Neural Networks (ANN) control involved. More information about these experiments could be find in the link publication (see <strong>related identifiers section</strong>).</p> <p>Basic code files to perform data analysis and ANN training are provided in the <strong>CodeOnline_2022_SPCA21 folder. </strong></p> <p>All the information needed to understand the structure of the <strong>DataOnline_2022_SPCA21 </strong>and <strong>CodeOnline_2022_SPCA21 </strong>folders and files are provided in <strong>CodeOnline_2022_SPCA21 folder.</strong></p> <p>The file <strong>SummaryOfFiles </strong>gives a description of all the files of the <strong>DataOnline_2022_SPCA21 folder,</strong> a <strong>file tree </strong>is also provided at the end of the document.</p> <p>The files <strong>MainDataExplained </strong>and <strong>SensorsDataExplained</strong> list and give a description of the variables recorded during experiments in the phase files (e.g. PHASE.json and PHASE_sensors.json respectively).</p> <p>The three <strong>Exp<em>X</em>FilesWorkflow</strong> <strong>files </strong>(with <em>X</em> =1,2,3) give an overview of the work-flow of experimental files creation during the <em>X</em> experiment.</p> <p>The CodeExplanations file lists and gives a description of code files available in the <strong>CodeOnline_2022_SPCA21 folder. </strong>The <strong>DependencyTree</strong> <strong>file</strong> shows the code organisation. The <strong>GuideInstall file</strong> contains information needed to run the code files properly.</p>
One Hand project - Transfer of prosthesis control skill after training in VR, data set pre-test post-test
Open the record for dataset details and reuse information.
Randomized, Sham-Controlled Investigation of the Leia Sensory Prosthesis in Individuals With Peripheral Neuropathy
ClinicalTrials.gov study NCT07236515. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Postoperative Scar in the Control Excess of Mobility Induced by Annulus Removal on Inserting a Lumbar Disc Prosthesis
ClinicalTrials.gov study NCT04641039. IPD Sharing: NO. Countries: 1. Publications: 3.
Data from: The effects of ground-irregularity-cancelling prosthesis control on balance over uneven surfaces
Open the record for dataset details and reuse information.
Data from: Evaluating internal model strength and performance of myoelectric prosthesis control strategies
Ongoing developments in myoelectric prosthesis control have provided prosthesis users with an assortment of control strategies that vary in reliability and performance. Many studies have focused on improving performance by providing feedback to the user, but have overlooked the effect of this feedback on internal model development, which is key to improving long-term performance. In this work, the strength of internal models developed for two commonly used myoelectric control strategies: raw control with raw feedback (using a regression-based approach), and filtered control with filtered feedback (using a classifier-based approach), were evaluated using two psychometric measures: trial-by-trial adaptation and just-noticeable-difference. The performance of both strategies was also evaluated using a Schmidt's style target acquisition task. Results obtained from 24 able-bodied subjects showed that although filtered control with filtered feedback had better short-term performance in path efficiency (p < 0.05), raw control with raw feedback resulted in stronger internal model development (p < 0.05), which may lead to better long-term performance. Despite inherent noise in the control signals of the regression controller, these findings suggest that rich feedback associated with regression control may be used to improve human understanding of the myoelectric control system.
Effects of Stress Ball and Hand Holdig on Pain and Mobility Levels During Continuous Passive Motion In Patients With Total Knee Prosthesis: A Randomized Controlled Trial
ClinicalTrials.gov study NCT06608264. IPD Sharing: NO. Countries: 1. Publications: 0.
RESCU System for Robust Upper Limb Prosthesis Control
ClinicalTrials.gov study NCT04043234. IPD Sharing: NO. Countries: 1. Publications: 0.
Intent Recognition for Prosthesis Control
ClinicalTrials.gov study NCT05537792. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of the Phantom X Implantable EMG Sensor System for Myoelectric Prosthesis Control
ClinicalTrials.gov study NCT07325708. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Data from: Evaluating internal model strength and performance of myoelectric prosthesis control strategies
Open the record for dataset details and reuse information.
Evaluation of a Neural-Controlled Powered Prosthesis Across Diverse Real-World Tasks
ClinicalTrials.gov study NCT07204912. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Targeted Reinnervation for Neuromas as a Means to Improve Prosthesis Control in Major Limb Amputation
ClinicalTrials.gov study NCT02316262. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Strategies to Control Robotic Hand Prosthesis Via HD-sEMG and to Restore Sensory Feedback Via TENS
ClinicalTrials.gov study NCT06486571. IPD Sharing: NO. Countries: 1. Publications: 0.
Effect of PEEK and Co-Cr Framework Reinforcement on Marginal Bone Loss Around Implants Supporting a Fixed All-on-four Prosthesis in Completely Edentulous Mandibles. A Randomized Controlled Clinial Tri
ClinicalTrials.gov study NCT06591611. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
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)
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.