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Detail publikace
HEJČ, J. ŘEDINA, R. KOLÁŘOVÁ, J. STÁREK, Z.
Originální název
Epycon: A Single-platform Python Package for Parsing and Converting Raw Electrophysiology Data into Open Formats
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
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 CommaSeparated 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.
Klíčová slova
Cardiac Electrophysiology Waveforms, Data Parsing Tool, Electrophysiology Data Access, Cardiac Electrogram Processing, Unprocessed Data Access
Autoři
HEJČ, J.; ŘEDINA, R.; KOLÁŘOVÁ, J.; STÁREK, Z.
Vydáno
20. 11. 2023
Nakladatel
IEEE Computer Society
ISSN
2325-887X
Periodikum
Computing in Cardiology
Ročník
50
Číslo
neuvedno
Stát
Spojené státy americké
Strany od
1
Strany do
4
Strany počet
URL
https://cinc.org/2023/Program/accepted/315_CinCFinalPDF.pdf
BibTex
@inproceedings{BUT185373, author="Jakub {Hejč} and Richard {Ředina} and Jana {Kolářová} and Zdeněk {Stárek}", title="Epycon: A Single-platform Python Package for Parsing and Converting Raw Electrophysiology Data into Open Formats", booktitle="Computing in Cardiology 2023", year="2023", series="50", journal="Computing in Cardiology", volume="50", number="neuvedno", pages="1--4", publisher="IEEE Computer Society", doi="10.22489/CinC.2023.315", issn="2325-887X", url="https://cinc.org/2023/Program/accepted/315_CinCFinalPDF.pdf" }