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Landajuela, Mikel; Anirudh, Rushil; Blake, Robert (2022). Dataset of Simulated Intracardiac Transmembrane Voltage Recordings and ECG Signals. In Lawrence Livermore National Laboratory (LLNL) Open Data Initiative. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0SN094N
- Description
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The dataset consists of pairs of computationally simulated intracardiac transmembrane voltage recordings and ECG signals. In total, 16140 organ-level simulations were conducted to create this dataset, using a range of cardiac geometries and physiological parameters. Simulations were performed at LLNL's Lassen supercomputer, concurrently utilizing 4 GPUs and 40 CPU cores. Each simulation produced pairs of 500ms-by-10 ECG signals and 500ms-by-75 transmembrane voltage signals. For convenience, the signals are concatenated and saved as matrices. Each of these matrices is then stored as a numpy array. See the documentation for further details.
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- Note
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This work was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights.
Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or Lawrence Livermore National Security, LLC.
The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes.
- Funding
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This work was performed under LDRD-18-LW-078 at Lawrence Livermore National Laboratory. Copyright (c) 2022, Lawrence Livermore National Security, LLC. Written by Mikel Landajuela (landajuelala1@llnl.gov). Release number - LLNL-MI-835833.
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Mikel Landajuela: https://orcid.org/0000-0002-4804-6513
Rushil Anirudh: https://orcid.org/0000-0002-4186-3502
Doi:
https://doi.org/10.6075/J0SN094N
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- License
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License
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- Lawrence Livermore National Laboratory
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Under copyright (US)
Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.
Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.
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Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)
- Last Modified
2022-10-06