Find research datasets worth reusing

ASPIRE: Adapting Self-Blood Pressure Monitoring to Reduce Health Disparities

ClinicalTrials.gov study NCT06175793. IPD Sharing: NO. Countries: 1. Publications: 2.

Monitoring of Hepatitis C Treatment Using Telemedicine - a Clinical Trial in Public Health System in Brazil

ClinicalTrials.gov study NCT04039698. IPD Sharing: YES. Countries: 1. Publications: 1.

University of California Health Remote (Home) Monitoring Evaluation

ClinicalTrials.gov study NCT05390502. IPD Sharing: Not stated. Countries: 1. Publications: 3.

Using Remote Monitoring to Address Health Disparities in Type 2 Diabetes

ClinicalTrials.gov study NCT06517576. IPD Sharing: NO. Countries: 1. Publications: 3.

Black Women's Life Experience On Cardiovascular Health Via Ongoing Monitoring

ClinicalTrials.gov study NCT06150989. IPD Sharing: YES. Countries: 1. Publications: 1.

DIMOH: New Digital Methods for Monitoring Oral Health. An in Vivo Assessment

ClinicalTrials.gov study NCT04050306. IPD Sharing: UNDECIDED. Countries: 2. Publications: 10.

Use of Continuous Glucose Monitoring in Non-Diabetic Population to Compliment Signos Mobile Health Platform

ClinicalTrials.gov study NCT05121844. IPD Sharing: NO. Countries: 1. Publications: 51.

A Study AnalyZing a NovEl Wearable SeNsor for Remote PatIent Health Monitoring

ClinicalTrials.gov study NCT03993886. IPD Sharing: NO. Countries: 1. Publications: 3.

TEC4Home Heart Failure: Using Home Health Monitoring to Support the Transition of Care

ClinicalTrials.gov study NCT03439384. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Digital Health Feedback System (DHFS) for Longitudinal Monitoring of ARVs Used in HIV Pre-exposure Prophylaxis (PrEP)

ClinicalTrials.gov study NCT03693040. IPD Sharing: Not stated. Countries: 1. Publications: 0.

Telephone Health Coaching and Remote Exercise Monitoring for Peripheral Artery Disease

ClinicalTrials.gov study NCT03496948. IPD Sharing: YES. Countries: 1. Publications: 23.

Tele-Health Electronic Monitoring to Reduce Post Discharge Complications and Surgical Site Infections

ClinicalTrials.gov study NCT02767011. IPD Sharing: NO. Countries: 0. Publications: 1.

opencc-by-4.0Jan 2020View details →

zenodo28/100

Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques?

This is a research compendium (RC) for the publication <blockquote> Monitoring forest health using hyperspectral imagery: Does feature selection improve the performance of machine-learning techniques? </blockquote> Code, figures, appendices and the manuscript can be found in the corresponding <a href="https://github.com/pat-s/2019-feature-selection">GitHub repository</a>. This RC is a static snapshot at the time of submission. The GitHub repository holds the latest version and may see changes after the publication was accepted. Data sources and description <ul> <li>aoi.gpkg: Area of interest for downloading Sentinel-2 images. Not used in the publication. Source: Custom.</li> <li>forest_mask.gpkg: A forest/non-forest mask of the Basque Country. Not used in the publication. Source: Custom.</li> <li>hyperspectral.zip: Hyperspectral remote sensing data used to extract reflectance values on the tree level. Source: Custom.</li> <li>plot-locations.gpkg: Spatial location of the plots used in the study. Source: Custom.</li> <li>tree-in-situ-data-corrected.zip: Corrected in-situ data containing defoliation information on the tree level. A correction of the spatial location was applied by the creators of the data. Source: Custom.</li> <li>tree-in-situ-data.zip: First version of in-situ data containing defoliation information on the tree level. Not used in the publication. Source: Custom.</li> </ul> Licenses All files are licensed under CC BY 4.0.

dryad28/100

Data from: Development of low cost non-contact structural health monitoring system for rotating machinery

Condition monitoring systems are increasingly being employed in industrial applications to improve the availability of equipment to increase the overall equipment efficiency. Condition monitoring of gearboxes, a key element of rotating machines, ensures to continuously reduce and eliminate costs, unscheduled downtime and unexpected breakdowns. This study demonstrates a low cost microcontroller based non-contact data acquisition system for condition monitoring of rotating machinery. Experimental validation of the proposed system was carried out by performing examination tests on a gearbox test-rig. A user friendly Graphical User Interface (GUI) was also developed which facilitate user to perform signal processing in both real-time and offline mode. With these features the proposed system can perform most of the functions available in complex, standalone machines. The use of a general purpose PC and standard programming language makes the system simple, economical, and adaptable to a variety of problems. The tests show the developed system can perform properly as proposed.

opencc-zeroDec 2017View details →

dryad28/100

Data from: The effect of promoting current local research activities on large monitors on the population's interest in health-related research – a randomized controlled trial

OBJECTIVE: The objectives of this study were threefold: to estimate people's interest in health-related research, to understand to what extent people appreciate being actively informed about current local health-related research and to investigate whether their interest can be influenced by advertising local current health-related research using large TV monitors. DESIGN: Randomized controlled trial using a stepped wedge design. SETTING: The emergency department waiting room at two public hospitals in northern Queensland, Australia. PARTICIPANTS: Waiting patients and their accompanying friends and relatives in the emergency department waiting room not requiring immediate medical attention. INTERVENTIONS: A TV monitor advertising local current health-related research. MAIN OUTCOME MEASURES: Odds ratio for the effect of intervention on changing the interest in health-related research compared to a control group while adjusting for gender, age and socioeconomic standard. RESULTS: The intervention significantly increased the short-term interest in health-related research with an odds ratio of 1.3 (1.1-1.7, p=0.0063). We also noted that being female and being older was correlated to a higher interest in health-related research CONCLUSIONS: This study found that proactive information significantly increased the general populations' interest in health-related research. There are reasonable set up costs involved but the costs for maintaining the system were very low. Hence, it seems reasonable that research-active organizations should give much higher priority to this type of activity. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) with the registration number ACTRN12617001085369

opencc-zeroJul 2019View details →

zenodo28/100

EFFICIENT GENERATION OF RECEIVER OPERATING CHARACTERISTICS FOR THE EVALUATION OF DAMAGE DETECTION IN PRACTICAL STRUCTURAL HEALTH MONITORING APPLICATIONS

Experimentally measured guided wave signal on a pipe over temperature cycles, used in the paper to construct synthetic datasets to evaluate performance of damage detection methods.

opencc-by-4.0Jan 2017View details →

zenodo28/100

Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin Plate

This repository contains a novel time-series dataset for impact detection and localization on a plastic thin-plate, towards Structural Health Monitoring applications, using ceramic piezoelectric transducers (PZTs) connected to an Internet of Things (IoT) device. The dataset was collected from an experimental procedure of low-velocity, low-energy impact events that includes at least 3 repetitions for each unique experiment, while the input measurements come from 4 PZT sensors placed at the corners of the plate. For each repetition and sensor, 5000 values are stored with 100 KHz sampling rate. The system is excited with a steel ball, and the height from which it is released varies from 10 cm to 20 cm. To the best of our knowledge, we are the first, to publish a public dataset that contains PZT sensors measurements concerning low-velocity, low-energy impact events in a thin plastic plate. In addition, we also contribute with our methodology on data collection using an SHM IoT system with resource constraints (based on Arduino NANO 33 MCU), as opposed to the majority of the literature that uses Oscilloscopes for data acquisition. This concept of an MCU-based system for data collection in SHM is especially important nowadays, due to the fast rise of extreme-edge and embedded machine learning practices solutions that enable a variety of real-time data-driven SHM applications. Finally, we wish to highlight that by using this specific Microcontroller Unit (MCU) and sensors, the proposed implementation aims for an overall low-cost data collection solution. The dataset has been published as a dataset paper in 20th ACM Conference on Embedded Networked Sensor Systems (SenSys 2022), in the following workshop:  The Fifth International Workshop on Data: Acquisition To Analysis (DATA '22). The dataset is also available at https://github.com/Smart-Objects/Impact-Events-Dataset.

opencc-by-4.0Oct 2022View details →

dryad28/100

Non-invasive monitoring of multiple wildlife health factors by fecal microbiome analysis

Fecal microbial biomarkers represent a less invasive alternative for acquiring information on wildlife populations than many traditional sampling methodologies. Our goal was to evaluate linkages between fecal microbiome communities in Rocky Mountain elk (Cervus canadensis) and four host factors including sex, age, population, and physical condition (body-fat). We paired a feature-selection algorithm with an LDA-classifier trained on elk differential bacterial abundance (16S-rRNA amplicon survey) to predict host health factors from 104 elk microbiomes across four elk populations. We validated the accuracy of the various classifier predictions with leave-one-out cross-validation using known measurements. We demonstrate that the elk fecal microbiome can predict the four host factors tested. Our results show that elk microbiomes respond to both the strong extrinsic factor of biogeography and simultaneously occurring, but more subtle, intrinsic forces of individual body-fat, sex, and age class. Thus, we have developed and described herein a generalizable approach to disentangle microbiome responses attributed to multiple host factors of varying strength from the same bacterial sequence data set. Wildlife conservation and management presents many challenges, but we demonstrate that non-invasive microbiome surveys from scat samples can provide alternative options for wildlife population monitoring. We believe that, with further validation, this method could be broadly applicable in other species and potentially predict other measurements. Our study can help guide the future development of microbiome-based monitoring of wildlife populations and supports hypothetical expectations found in host-microbiome theory.

opencc-zeroJan 2023View details →

ClinicalTrials.gov28/100

Blood Glucose Monitoring in Electronic Health Records

ClinicalTrials.gov study NCT03542487. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.

ClinicalTrials.gov28/100

Partners in Control, Phase II: Using Remote Monitoring Technology With Community Health Workers to Support Hypertension Management for Latinx Patients

ClinicalTrials.gov study NCT06730230. IPD Sharing: YES. Countries: 1. Publications: 0.