Python (3.8.10) dependencies:
- matplotlib (3.4.2), numpy (1.19.5), scipy (1.6.3), pandas (1.2.4), seaborn (0.11.1, optional)
- torch (1.10.2+cu113)
- wfdb (3.3.0)
- import_ipynb (0.1.3)
To minimize conflict, our versions are given as reference.
- Download the MIT-BIH Arrhythmia Database.
- Run ecg_beat_extraction.ipynb twice to generate single beats and beat-trios.
- There should be 6 files generated.
- Run ecg_dataset_preparation.ipynb twice to generate datasets from single beats and beat-trios.
- This generates dictionaries for each user. Save the dictionaries for single beats (and optionally for beat-trios).
- We perform domain adaptation at this stage using the generated dictionaries for each user.
- There should be 68 dataset files generated, and dictionaries for each user.
- To train your own classifier, go to train.ipynb. Otherwise, skip this part.
- To test with pretrained weights go to pretrained_*.ipynb files.