Pyheartlib is a Python package for processing electrocardiogram (ECG) recordings. This software facilitates working with signals for tasks such as heartbeat detection, heartbeat classification, and arrhythmia classification. Utilizing it, researchers can focus on these tasks without the burden of designing data processing modules. The package transforms original data into processed signal excerpts and their computed features in order to be used for training various machine learning models including advanced deep learning models, which can be trained by taking advantage of Keras and Tensorflow libraries.
Documentation is available at the link below.
Current version of the package was tested on:
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Ubuntu: 20.04 | 22.04 & Python: 3.10 | 3.11 & Processor: x86_64
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macOS: 12.6.9 | 13.6 & Python: 3.10 | 3.11 & Processor: x86_64
However, it may also be compatible with other systems.
The package can be installed with pip:
$ pip install pyheartlibExamples can be found in the examples section of the documentation and also in the GitHub repository (examples).
To cite this software, please use:
Mohammadi, S., (2024). Pyheartlib: A Python package for processing electrocardiogram signals. Journal of Open Source Software, 9(95), 5792, https://doi.org/10.21105/joss.05792
BibTeX:
@article{devnums_pyheartlib_2024,
doi = {10.21105/joss.05792},
url = {https://doi.org/10.21105/joss.05792},
year = {2024},
publisher = {The Open Journal},
volume = {9},
number = {95},
pages = {5792},
author = {Sadegh Mohammadi},
title = {Pyheartlib: A Python package for processing electrocardiogram signals},
journal = {Journal of Open Source Software}
}
Feedback and contributions are appreciated. The guidelines for contributing are provided here.
For any questions, discussions, or problems with this software, please join us on Discord. An alternative option is to open a GitHub issue. (Issues, New issue)
Pyheartlib is released under the AGPL-3.0-only License.