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29 results for “Electrocardiogram (ECG)”
Surface electrocardiogram (ECG) dataset recorded during relaxation in 70 healthy subjects
<p><strong>Study Sample and Ethics Statement</strong></p> <p>The sample consisted of 71 university students, average age 20.38 years (<em>SD</em> = 2.96), 78.8% female. Subjects with previous cardio-vascular disorders and irregular ECG were excluded. The study has been approved by the Institutional Review Board of the Department of Psychology, University of Belgrade No. 2018-19. All participants signed Informed Consents in accordance with the Declaration of Helsinki.</p> <p>In the course of visual examination, it was decided to discard ECG from one subject due to the presence of bigeminial arythmia, so further analysis was performed on 70 subjects instead of 71.</p> <p><strong>Measurement Setup</strong></p> <p>BIOPAC sensors (Biopac Systems Inc., Camino Goleta, CA, USA) were used for recording biosignals in another study (<a href="http://empirijskaistrazivanja.org/wp-content/uploads/2021/04/EIP2020_conf_proceedings.pdf#page=17">Bjegojević et al., 2020</a>). Here, we used only ECG signals recorded in sitting relaxed position from standard bipolar Lead I using the BIOPAC MP150 unit with AcqKnowledge software and ECG 100C module with surface H135SG Ag/AgCl electrodes (Kendall/Covidien, Dublin, Ireland). In order to decrease skin-electrode impedance, the skin was cleaned with Nuprep gel (Weaver & Co., Aurora, USA) to reduce skin-electrode impedance. The sampling frequency was set at 2000 Hz and the gain was set to 1000.</p> <p>ECG signals were recorded during relaxation in a sitting position and data were recorded during 2 min long intervals. More information is available in the article [<a href="https://onlinelibrary.wiley.com/doi/10.1111/anec.12919">1</a>].</p> <p><strong>Dataset, Code, and Feature Extraction Instructions</strong></p> <ol> <li><a href="https://zenodo.org/record/5736849/files/analysisECG.R?download=1">analysisECG.R</a>, function with analysis procedures written in <a href="https://www.r-project.org/">R programming language</a></li> <li><a href="https://zenodo.org/record/5736849/files/anec12919-sup-0001-supinfo.pdf?download=1">anec12919-sup-0001-supinfo.pdf</a>, detailed ECG processing and feature extraction procedure (also available as <a href="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2Fanec.12919&file=anec12919-sup-0001-Supinfo.docx">supplementary material</a> for article [<a href="https://onlinelibrary.wiley.com/doi/10.1111/anec.12919">1</a>])</li> <li><a href="https://zenodo.org/record/5736849/files/ecg_70.txt?download=1">ecg_70.txt</a>, .txt data file, text format</li> <li><a href="https://zenodo.org/record/5736849/files/mainECG.R?download=1">mainECG.R</a>, a main program written in R programming language</li> <li><a href="https://zenodo.org/record/5736849/files/R-studio-version-info.txt?download=1">R-studio-version-info.txt</a>, the version of <a href="https://www.rstudio.com/">R Studio</a> where the code was tested</li> <li><a href="https://zenodo.org/record/5736849/files/R-version-info.txt?download=1">R-version-info.txt</a><a href="https://zenodo.org/api/files/aa8d999e-1b08-44b5-883f-0540afe8feb8/R-version-info.txt"> </a>, the version of R programming language where the code was tested</li> </ol> <p>For ECG-based feature extraction, we used the following R packages:</p> <ol> <li><strong>signal</strong> - Signal Processing Functions (signal developers (2014). <em>signal: Signal processing</em>. <a href="http://r-forge.r-project.org/projects/signal/">http://r-forge.r-project.org/projects/signal/</a>)</li> <li><strong>pracma</strong> - Practical Numerical Math Functions ( Borchers, H. W. (2019). <em>Package ‘pracma’: Practical numerical math functions</em>. R package version, 2(1). <a href="https://CRAN.R-project.org/package=pracma">https://CRAN.R-project.org/package=pracma</a>)</li> </ol> <p>Please, note that the results of personality trait tests are not available in the current dataset. We are planning to open them in our future research. For more information and planned availability in open access, please, contact the corresponding author of [<a href="https://onlinelibrary.wiley.com/doi/10.1111/anec.12919">1</a>] by e-mail (<a href="mailto:nadica.miljkovic@etf.bg.ac.rs">nadica.miljkovic@etf.bg.ac.rs</a>).</p> <p><strong>Citing Instruction</strong></p> <p>If you find these signals and code useful for your own research or teaching class, please cite relevant dataset and supporting publications:</p> <ol> <li> <p>Boljanić, T., Miljković, N., Lazarević, L. B., Knežević, G., & Milašinović, G. (2021). Relationship between electrocardiogram-based features and personality traits: Machine learning approach. <em>Annals of Noninvasive Electrocardiology</em>, 00, e12919. <a href="https://doi.org/10.1111/anec.12919">https://doi.org/10.1111/anec.12919</a></p> </li> <li> <p>Bjegojević, B., Milosavljević, N., Dubljević, O., Purić, D., & Knežević, G. (2020). <a href="http://empirijskaistrazivanja.org/wp-content/uploads/2021/04/EIP2020_conf_proceedings.pdf#page=17">In pursuit of objectivity: Physiological measures as a means of emotion induction procedure validation</a>. <em>XXIVI Scientific Conference on Empirical Studies in Psychology</em>, p. 17-19.</p> </li> <li> <p>Boljanić, T., Miljković, N., Lazarević B. Lj., Knežević, G., & Milašinović, G. (2021). Surface electrocardiogram (ECG) dataset recorded during relaxation in 70 healthy subjects (Version 1) [Data set]. <em>Zenodo</em>. <a href="https://doi.org/10.5281/zenodo.5599239">https://doi.org/10.5281/zenodo.5599239</a></p> </li> </ol>
Electrocardiogram (ECG) Guided Peripherally Inserted Central Catheter (PICC) Placement
ClinicalTrials.gov study NCT00742053. IPD Sharing: NO. Countries: 1. Publications: 1.
The Effect of Buprenorphine Delivered by Buprenorphine Transdermal System (BTDS) at Doses up to 80 Micrograms/Hour (mcg/hr) and Naltrexone on Electrocardiogram (ECG) Intervals in Healthy Volunteers
ClinicalTrials.gov study NCT01999114. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Home Electrocardiogram (ECG) Monitoring After Heart Transplantation
ClinicalTrials.gov study NCT01365806. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Ultra-High Frequency - Electrocardiogram (UHF-ECG) for the Diagnosis of Ventricular Electrical Dyssynchrony (VED)
ClinicalTrials.gov study NCT06641362. IPD Sharing: NO. Countries: 3. Publications: 2.
Study Comparing In-laboratory Polysomnography Electrocardiogram (PSG ECG) to Simultaneously Recorded In-laboratory ECG on the CPC M1 Device
ClinicalTrials.gov study NCT01234077. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Evaluating Electrocardiogram (ECG) Abnormalities From Young Adulthood Through Middle Age
ClinicalTrials.gov study NCT00556751. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: A qualitative study on the development and rectification of advanced medical students' misconceptions about the physiological electrocardiogram (ECG)
<p><strong>Purpose:</strong> The study takes a qualitative and explorative approach to capture the concepts that German medical students have of the physiological electrocardiogram (ECG) which they acquired during their preclinical training. These concepts are then considered for possible misconceptions. Afterwards a theory-based intervention which allows subjects to see the connection of the curve progression with the spatial spreading of excitation (animated vector loop) is put to the test.</p> <p><strong>Methods:</strong> In the course of a diagnosis of learning potentials, individual students participated in problem-centred, guided interviews. The developed intervention was tested in separately conducted teaching experiments using thinking aloud protocols. The data evaluation was done through qualitative content analysis. Based on the conceptual metaphor theory, conceptions and their underlying embodied cognition were analysed.</p> <p><strong>Results: </strong>One of the subjects' typical misinterpretations is taking the progression of the ECG tracing for a mere increase and decrease of the myocardium's electrical activity, rather than connecting it with its spatial and temporal aspects. The data evaluation has shown that the newly developed theory-based intervention can lead to re-learning. Reconstructed metaphorical concepts illustrate this process of understanding. It is exemplarily shown how, through the course of the interviews, students are enabled to appropriately explain ECGs as the two-dimensional representation of the spatial excitation propagation in the heart.</p> <p><strong>Conclusion: </strong>By capturing typical misconceptions of the physiological electrocardiogram and demonstrating interventions that support learning, the study provides a contribution to comprehensive learning which can be used in the basic education of medical students.</p>
Validation of the Performance of the Electrocardiogram (ECG) Function in the Masimo INVSENSOR00057
ClinicalTrials.gov study NCT06071754. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Pharmacokinetic and Exploratory Electrocardiogram (ECG) Study
ClinicalTrials.gov study NCT01018420. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Leadless Electrocardiogram (ECG) Evaluation Study
ClinicalTrials.gov study NCT01297283. IPD Sharing: NO. Countries: 1. Publications: 0.
Data from: A qualitative study on the development and rectification of advanced medical students’ misconceptions about the physiological electrocardiogram (ECG)
Open the record for dataset details and reuse information.
Safety Study of Electrocardiogram (ECG) Effects of Sancuso® (Granisetron TDS)
ClinicalTrials.gov study NCT00890565. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Study to Evaluate the QTC Interval in Healthy Volunteers Dosed With Dexpramipexole (QTC = Electrocardiogram (ECG) Interval Measured From the Onset of the QRS Complex to the End of the T Wave Corrected
ClinicalTrials.gov study NCT01511029. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Artificial Intelligence (AI) Analysis of Synchronized Phonocardiography (PCG) and Electrocardiogram(ECG)
ClinicalTrials.gov study NCT06009718. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Comparison of a Torso-Based Derived 6-Lead Electrocardiogram (ECG) Device With Standard 12-Lead Electrocardiogram (ECG) in Healthy Volunteers
ClinicalTrials.gov study NCT07277374. IPD Sharing: NO. Countries: 1. Publications: 0.
Intracoronary Electrocardiogram (ECG) and Myonecrosis After Bifurcation Stenting
ClinicalTrials.gov study NCT01268228. IPD Sharing: Not stated. Countries: 2. Publications: 0.
Cognitive Function and Electrocardiogram (ECG) During Hypoglycemia and Blockade of the Renin-angiotensin System
ClinicalTrials.gov study NCT01116180. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Evaluation of Dose-Dependent Repeated-Dose Neramexane Effects on Cardiac Repolarisation (QT/QTc Interval Duration): Electrocardiogram (ECG) Study in Healthy Adult Subjects
ClinicalTrials.gov study NCT00978614. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effect of Methylnaltrexone (MNTX) on Electrocardiogram (ECG) Parameters and Cardiac Repolarization
ClinicalTrials.gov study NCT01363323. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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