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benchmarks of CinC and CPSC challenges, and using other databases

a large part are migrated from other DeepPSP repositories, some are implemented in the old fasion, being inconsistent with the new system architecture of torch_ecg, hence need updating and testing

Benchmark Architecture Source Finished Updated Tested
CinC2020 CRNN DeepPSP/cinc2020 ✔️ ✔️ ✔️
CinC2021 CRNN DeepPSP/cinc2021 ✔️ ✔️ ✔️
CinC20221 Multi Task Learning (MTL) DeepPSP/cinc2022 ✔️ ✔️ ✔️
CPSC2019 SequenceTagging/U-Net NA ✔️ ✔️ ✔️
CPSC2020 CRNN/SequenceTagging DeepPSP/cpsc2020 ✔️ ❌ ❌
CPSC2021 CRNN/SequenceTagging/LSTM DeepPSP/cpsc2021 ✔️ ✔️ ✔️
LUDB U-Net NA ✔️ ✔️ ✔️

Known Issues

  1. Slicing data for CPSC2021 is too slow. An offline generated (sliced) dataset is hosted at Kaggle.
  2. Dataset for LUDB is too slow
  3. cli for training models are completely not tested

Footnotes

  1. Although CinC2022 dealt with acoustic cardiac signals (phonocardiogram, PCG), the tasks and signals can be treated similarly. ↩