DeepECG

This repository hosts the project for the Biomedical Signal and image Processing (BiSP) Lab at the University of Milan (Italy), focusing on ECG-based biometric recognition. The project is based on the methodology described by (Deep-ECG article) and utilizes the Smart Health for Assessing the Risk of Events via ECG Database.

Requirements

To start the program you're gonna need:

• Python 3.9 -> more info you can find https://www.python.org/downloads/release/python-390/
• pip -> more info about installation you can find https://pip.pypa.io/en/stable/cli/pip_install/
• git -> more info you can find https://git-scm.com/download/win
• virtual environment (venv) -> more info you can find https://virtualenv.pypa.io/en/stable/installation.html

Seting up the virtual enviroment

1. in Command Line go to cloned DeepECG repository. Create virtual environment - after this you shuld have aditional folfer venv

C:\path\DeepECG> python -m venv C:\path\DeepECG\venv

1. activate environment - after this step (venv) should appear before path in the line

C:\path\DeepECG> C:\path_to_program\DeepECG\venv\Scripts\activate

1. install requirements

(venv) C:\path\DeepECG> pip install -r requirements.txt

Pipeline

1. preprocessing and saving the data

(venv) C:\path\DeepECG> python preprocess 'path/to/data' 'path/to/saving/directory'

1. running the experiments

(venv) C:\path\DeepECG> python run_exp_1.py 'path/to/preprocessed/data'

Authors

Zofia Mizgalewicz

Christian R. Cuenca

Dr. Massimo W. Rivolta

Prof. Roberto Sassi

Prof. Fabio Scotti

Links

To see whats happaning in the BiSP

For more details on the dataset, visit SHAREEDB