This repository contains ECG - an open-source library for assisting in diagnostics of heart conditions from ECG. This library provides functionality of heart condition detection, differential diagnostics, and risk markers evaluation. The library handles ECGs in both formats, as signal or as a photo.
Project Description
ECG Features
Main features implemented in the library
- Recognition of ECG signal from a photo of printed ECG
- Detection of ST-elevation
- IM risk markers evaluation
- IM/BER differential diagnosis
Thus compared to other frameworks, ECG:
- Handles ECGs provised as a signal as well as an image
- Provides a range of functionality useful for IM diagnostics
Details of implemented methods.
Data Requirement
- Required ECG frequency: 500 Hz
- Required length: ≥ 5s
Installation
Requirements: Python 3.7
- [optional] create Python environment, e.g.
$ conda create -n ECG python=3.7 $ conda activate ECG - install requirements from requirements.txt
$ pip install -r requirements.txt - install the library as a package
$ python -m pip install git+ssh://git@github.com/tanyapole/ECG
Development
Environment
Requirements: Python 3.7
- [optional] create Python environment, e.g.
$ conda create -n ECG python=3.7 $ conda activate ECG - clone repository and install all requirements
$ git clone git@github.com:tanyapole/ECG.git $ cd ECG $ pip install -r requirements.txt - run tests
$ pytest tests/api_tests.py - build a PyPi package locally
$ python3 -m pip install --upgrade build $ python3 -m build
Documentation
The general description is available here.
Examples & Tutorials
We provide a tutorial demonstrating suggested usage pipeline
Contribution Guide
The contribution guide is available in the repository.
Acknowledgments
We acknowledge the contributors for their important impact and the participants of the numerous scientific conferences and workshops for their valuable advice and suggestions.
Contacts
TBD
Citation
TBD