Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks

This repository includes the implentation of R peak detection method in Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks.

Network Architecture

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_selfONN.py

Citation

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

@article{gabbouj2022robust,
  title={Robust Peak Detection for Holter ECGs by Self-Organized Operational Neural Networks},
  author={Gabbouj, Moncef and Kiranyaz, Serkan and Malik, Junaid and Zahid, Muhammad Uzair and Ince, Turker and Chowdhury, Muhammad EH and Khandakar, Amith and Tahir, Anas},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2022},
  publisher={IEEE}
}