/SSL-ECGv2

Official code repository of our work on stress detection using ECG-based self-supervised learning.

Primary LanguagePythonOtherNOASSERTION

"Detection of Stress with Self-supervised Learning" (TF v1.14.0)

Detection of Maternal and Fetal Stress from ECG with Self-supervised Representation Learning Authors: Sarkar et al.

Requirements

  • Python >=3.6
  • TensorFlow = 1.14.0
  • TensorBoard = 1.14.0
  • Scikit-Learn = 0.22.2
  • NumPy = 1.18.4
  • Tqdm = 4.36.1
  • Pandas = 0.25.1
  • Mlxtend = 0.17.0

Pre-trained Model

Self supervised pretrained model on public datasets is available here.

Citation

Please cite our papers for any purpose of usage.

@misc{sarkar2020detection,
      title={Detection of Maternal and Fetal Stress from ECG with Self-supervised Representation Learning}, 
      author={Pritam Sarkar and Silvia Lobmaier and Bibiana Fabre and Gabriela Berg and Alexander Mueller and Martin G. Frasch and Marta C. Antonelli and Ali Etemad},
      year={2020},
      eprint={2011.02000},
      archivePrefix={arXiv},
      primaryClass={q-bio.QM}
}

Acknowledgement

Codes are borrowed from SSL-ECG

Question

If you have any query or want to chat with me regarding our work please reach me at pritam.sarkar@queensu.ca or connect me in LinkedIN.