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@inproceedings{2424459,
author = {Hejc, Jakub and Redina, Richard and Kolarova, Jana and Stárek, Zdeněk},
address = {Atlanta},
booktitle = {2023 Computing in Cardiology},
doi = {http://dx.doi.org/10.22489/CinC.2023.315},
editor = {Christine Pickett, Cristiana Corsi, Rob MacLeod},
keywords = {Epycon},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Atlanta},
isbn = {979-8-3503-8252-5},
pages = {1-4},
publisher = {IEEE},
title = {Epycon: A Single-Platform Python Package for Parsing and Converting Raw Electrophysiology Data into Open Formats},
url = {https://ieeexplore.ieee.org/document/10364084},
year = {2023}
}
TY - JOUR
ID - 2424459
AU - Hejc, Jakub - Redina, Richard - Kolarova, Jana - Stárek, Zdeněk
PY - 2023
TI - Epycon: A Single-Platform Python Package for Parsing and Converting Raw Electrophysiology Data into Open Formats
PB - IEEE
CY - Atlanta
SN - 9798350382525
KW - Epycon
UR - https://ieeexplore.ieee.org/document/10364084
N2 - The WorkMate™ platform is a widely used system for recording and analyzing cardiac electrophysiology waveforms recorded during interventional procedures. However, the internal export tools do not usually allow full access to unprocessed data, which challenges its use for research purposes. The Epycon package is a data parsing tool that enables direct access to raw unipolar/bipolar waveforms and clinical annotations stored in WorkMate™ proprietary serialized file formats. It provides the ability to convert the data into established open formats, including Comma- Separated Values and Hierarchical Data Format 5. Epycon offers a number of features that make it a valuable tool for researchers, including memory-efficient batch processing, support for both raw unipolar and bipolar waveforms, and comprehensive documentation of WorkMate™ file format for development purposes. Epycon is implemented in Python 3.8 and can help researchers to more efficiently access electrophysiology data, facilitating research in developing algorithms for cardiac electrogram processing or creating open-source databases of electrophysiology data for public use.
ER -
HEJC, Jakub, Richard REDINA, Jana KOLAROVA and Zdeněk STÁREK. Epycon: A Single-Platform Python Package for Parsing and Converting Raw Electrophysiology Data into Open Formats. Online. In Christine Pickett, Cristiana Corsi, Rob MacLeod. \textit{2023 Computing in Cardiology}. Atlanta: IEEE, 2023, p.~1-4. ISBN~979-8-3503-8252-5. Available from: https://dx.doi.org/10.22489/CinC.2023.315.
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