Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network

This repository includes the implentation of R peak detection method in Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network.

Network Architecture

Verification Model

Dataset

• The China Physiological Signal Challenge 2020, (CPSC-2020) dataset is used for training & testing.
• R peak annotations are already available in the data folder.

Run

Train

• Download CPSC data from the link to the "data/" folder
• Data Preparation without augmentation

  python prepare_data.py

• Data Preparation with augmentation

  python prepare_data_augmentation.py

• Start patient wise training and evaluation.

  python run_cnn.py

Citation

If you use the provided method in this repository, please cite the following paper:

@article{zahid2021robust,
  title={Robust R-Peak Detection in Low-Quality Holter ECGs Using 1D Convolutional Neural Network},
  author={Zahid, Muhammad Uzair and Kiranyaz, Serkan and Ince, Turker and Devecioglu, Ozer Can and Chowdhury, Muhammad EH and Khandakar, Amith and Tahir, Anas and Gabbouj, Moncef},
  journal={IEEE Transactions on Biomedical Engineering},
  volume={69},
  number={1},
  pages={119--128},
  year={2021},
  publisher={IEEE}
}