rostepifanov/ecgmentations

A Python library for ecg data augmentation. Useful for machine learning.

42
/ 100
Emerging

Ecgmentations helps machine learning researchers and data scientists working with electrocardiogram (ECG) data. It takes existing ECG recordings and generates diverse new variations, which are then used to improve the accuracy and robustness of deep learning models trained to interpret ECGs. The output is augmented ECG datasets ready for model training.

No commits in the last 6 months. Available on PyPI.

Use this if you need to expand your ECG dataset to train more robust and accurate deep learning models for cardiac analysis.

Not ideal if you are looking for tools to directly analyze ECG signals or diagnose medical conditions, as this is a data preparation tool for machine learning.

cardiology biomedical-signal-processing medical-ai deep-learning-data-preparation healthcare-analytics
Stale 6m
Maintenance 0 / 25
Adoption 6 / 25
Maturity 25 / 25
Community 11 / 25

How are scores calculated?

Stars

22

Forks

3

Language

Python

License

MIT

Last pushed

Mar 10, 2025

Commits (30d)

0

Dependencies

3

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/rostepifanov/ecgmentations"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.