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10,068 results for “heart”
Figure 1 in Heart rate response and bimodal gas eXchange in three developmental stages of the bullfrog Lithobates catesbeianus (Anura: Ranidae)
Figure 1. Scheme of non-invasive apparatus to measure gas exchange in water (A) and air (B), and heart rate (C).
Figure 4 in Heart rate response and bimodal gas eXchange in three developmental stages of the bullfrog Lithobates catesbeianus (Anura: Ranidae)
Figure 4. Mass-specific oxygen consumption (A) and carbon dioxide released (B) for aerial (red lines and points) and aquatic (blue lines and points) gas exchange during development of Lithobates catesbeianus.
Figure 5 in Heart rate response and bimodal gas eXchange in three developmental stages of the bullfrog Lithobates catesbeianus (Anura: Ranidae)
Figure 5. Relationship between Log whole-body oxygen consumption (A) and carbon dioxide release (B) (µmol h-1) in 10 air (filled symbols) and water (open symbols), and Log10 body mass (g) in larval (blue triangles), premetamorphic (orange squares) and metamorphic (green circles) stages of Lithobates catesbeianus. Each point represents a measurement from a single animal. The regression lines correspond to aerial (red) and aquatic (blue) gas exchange. Dotted lines represent no significant correlation.
Validation of heart rate measurement of Fitbit Charge 4 and Xiaomi Mi Band 5
<p>Database containig data from heart rate validation study of 2 wristbands: Fitbit Charge 4 and Xiaomi Mi Band 5.</p>
An Open-access Database for the Evaluation of Cardio-mechanical Signals from Patients with Valvular Heart Diseases
<p>This dataset is for the paper "An Open-access Database for the Evaluation of Cardio-mechanical Signals from Patients with Valvular Heart Diseases" published to Frontiers in Physiology. Please cite "Yang C, Fan F, Aranoff N, Green P, Li Y, Liu C and Tavassolian N (2021) An Open-Access Database for the Evaluation of Cardio-Mechanical Signals From Patients With Valvular Heart Diseases.<br> Front. Physiol. 12:750221. doi: 10.3389/fphys.2021.750221" when using this database.</p> <p>The archive comprises SCG and GCG recordings sourced from and processed at multiple sites worldwide, including Columbia University Medical Center and Stevens Institute of Technology in the USA, as well as Southeast University, Nanjing Medical University, and the first affiliated hospital of Nanjing Medical University in China. It includes electrocardiogram (ECG), SCG, and GCG recordings collected from 100 patients with various conditions of valvular heart diseases, such as aortic and mitral stenosis. The recordings were collected from clinical environments with the same types of wearable sensor patch. Besides the raw recordings of ECG, SCG and GCG signals, a set of hand-corrected fiducial point annotations is provided by manually checking the results of the annotated algorithm. The database also includes relevant echocardiogram parameters associated with each subject such as ejection fraction, valve area, and mean gradient pressure.</p>
Cell to Whole Organ Global Sensitivity Analysis on a Four-chamber Heart Electromechanics Model Using Gaussian Processes Emulators - Training Datasets
<p>This database contains all training datasets for the Gaussian processes emulators (GPEs) trained in the study entitled "Cell to Whole Organ Global Sensitivity Analysis on a Four-chamber Electromechanics Model Using Gaussian Processes Emulators", submitted to PLOS Computational Biology.</p> <p>Every folder contains two csv files:</p> <p>- parameters.csv: the rows are the samples and the columns represent the parameters that were varied in the analysis</p> <p>- outputs.csv: the rows are the samples and the columns represent the values for the output features simulated for each sample</p> <p>In ventricular_cell_model, there are four folders:</p> <p>- ionic: ToR-ORd model samples used to train GPEs to predict the ventricular calcium transient features</p> <p>- contraction_isometric_stretch1.0: ToR-ORd model coupled with the Land contraction model samples used to train GPEs to predict the ventricular active tension transient features. The simulations were isometric contractions with no strain (or stretch 1.0).</p> <p>- contraction_isometric_stretch1.1: ToR-ORd model coupled with the Land contraction model samples used to train GPEs to predict the ventricular active tension transient features. The simulations were isometric contractions with 0.1 strain (or stretch 1.1).</p> <p>- contraction_isotonic: ToR-ORd model coupled with the Land contraction model samples used to train GPEs to predict the ventricular active tension transient features. The simulations were isotonic.</p> <p>The folder atrial_contraction_model follows the same structure, but the ionic model was Courtemanche, used to represent an atrial rather than ventricular calcium transient.</p> <p>The folder tissue_electrophysiology contains the training dataset for the GPEs to predict total atrial and ventricular activation times with an Eikonal model.</p> <p>The folder passive_mechanics contains the training dataset for the GPEs to predict inflated volumes and mean atrial and ventricular fiber strains for a passive inflation.</p> <p>The folder CircAdapt contains the training dataset for the GPEs to predict four-chamber pressure and volume features with the CircAdapt ODE model.</p> <p>Finally, the folder fourchamber contains the samples generated with a 3D-0D four-chamber electromechanics model to predict pressure and volume biomarkers for cardiac function.</p> <p>The details about the model can be found in the original publication.</p>
Data for Project 'Test-Retest Reliability and Validity of vagally-mediated Heart Rate Variability to Monitor Internal Training Load in Older Adults: A within-subjects (repeated-measures) randomized study'
<p>Data for Project 'Test-Retest Reliability and Validity of vagally-mediated Heart Rate Variability to Monitor Internal Training Load in Older Adults: A within-subjects (repeated-measures) randomized study' consisting of (1) the original and complete dataset ('Data_Brain-IT-Reliability-of-HRV-during-Exergaming_for-publication'; and (2) a corresponding README file including (a) general information, (b) data and file overview, (c) sharing and access information, (d) methodological information, and (e) data-specific information.</p>
Wrist-worn sensor validation for heart rate variability and electrodermal activity detection in a stressful driving environment
<p>The current dataset contributes to assess the accuracy of the Empatica 4 (E4) wristband for the detection of heart rate variability (HRV) and electrodermal activity (EDA) metrics in stress-inducing conditions and growing-risk driving scenarios. Heart Rate Variability (HRV) and ElectroDermal Activity (EDA) signals were recorded over six experimental conditions (i.e., Baseline, Video Clip, Scream, No Risk Driving, Low-Risk Driving, and High-Risk Driving) and by means of two measurement systems: the E4 device and a gold standard system. The raw quality of the physiological signals was enhanced by means of robust semi-automatic reconstruction algorithms. Heart Rate Variability time-domain parameters showed high accuracy in motion-free experimental conditions, while Heart Rate Variability frequency-domain parameters reported sufficient accuracy in almost every experimental condition.</p>
Neuromodulation to Treat Patients With Heart Failure With Preserved Ejection Fraction
ClinicalTrials.gov study NCT03327649. IPD Sharing: YES. Countries: 1. Publications: 2.
A Proof of Concept and Dose-finding Study of XXB750 in Patients With Heart Failure
ClinicalTrials.gov study NCT06142383. IPD Sharing: YES. Countries: 12. Publications: 0.
Reducing Hopelessness Through Improved Physical Activity in Adults With Heart Disease: With COVID-19 Considerations
ClinicalTrials.gov study NCT03907891. IPD Sharing: YES. Countries: 1. Publications: 5.
Mind Your Heart Study
ClinicalTrials.gov study NCT03571581. IPD Sharing: YES. Countries: 1. Publications: 2.
Prospective ARNI vs ACE Inhibitor Trial to DetermIne Superiority in Reducing Heart Failure Events After MI
ClinicalTrials.gov study NCT02924727. IPD Sharing: YES. Countries: 41. Publications: 9.
Inflammation and the Heart
ClinicalTrials.gov study NCT01589770. IPD Sharing: YES. Countries: 1. Publications: 1.
Effect of Sotagliflozin on Cardiovascular Events in Participants With Type 2 Diabetes Post Worsening Heart Failure (SOLOIST-WHF Trial)
ClinicalTrials.gov study NCT03521934. IPD Sharing: YES. Countries: 32. Publications: 6.
Comparison of Sacubitril/Valsartan Versus Enalapril on Effect on NT-proBNP in Patients Stabilized From an Acute Heart Failure Episode.
ClinicalTrials.gov study NCT02554890. IPD Sharing: YES. Countries: 1. Publications: 8.
DAA Treatment in Donor HCV-positive to Recipient HCV-negative Heart Transplant
ClinicalTrials.gov study NCT03208244. IPD Sharing: YES. Countries: 1. Publications: 1.
Study to Evaluate Safety, Tolerability, Pharmacokinetics and Pharmacodynamics of LCZ696 Followed by a 52-week, Double-blind Study of LCZ696 Compared With Enalapril in Pediatric Patients With Heart Fai
ClinicalTrials.gov study NCT02678312. IPD Sharing: YES. Countries: 29. Publications: 2.
Nordic Everolimus (Certican) Trial in Heart and Lung Transplantation
ClinicalTrials.gov study NCT00377962. IPD Sharing: UNDECIDED. Countries: 3. Publications: 3.
Efficacy and Safety of LCZ696 Compared to Valsartan, on Morbidity and Mortality in Heart Failure Patients With Preserved Ejection Fraction
ClinicalTrials.gov study NCT01920711. IPD Sharing: YES. Countries: 43. Publications: 55.
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.