tommy44458 / sleeptransformer

SleepTransformer

• Huy Phan, Kaare Mikkelsen, Oliver Y. Chén, Philipp Koch, Alfred Mertins, and Maarten De Vos. SleepTransformer: Automatic Sleep Staging With Interpretability and Uncertainty Quantification. IEEE Transactions on Biomedical Engineering (TBME), vol. 69, no. 8, pp. 2456-2467, 2022. [PDF] [Preprint]
  

These are source code and experimental setup for SHHS.

How to use:

1. Download the database SHHS. This may require to apply for licences. Information on how to obtain it can be found in the corresponding website.
2. To prepare data run shhs_data.m
3. Split data and generate file lists run data_split_eval.m run genlist_scratch_training.m (Not: I have included the "data_split_eval.mat" file and the "file_list" folder, you dont have to run this step again)
4. Training and evaluation run bash scripts in "scratch_training/sleeptransformer". The environment I used was Tensorflow 1.13, Python 3.7
5. Run matlab scripts in "evaluation" folders to aggregate the network outputs and compute metrics for example, run aggregate_sleeptransformer.m

The model weights trained on SHHS are available at https://zenodo.org/record/7927282 for reproducing the results in the paper.

Environment:

• Matlab v7.3 (for data preparation)
• Python3.7
• Tensorflow GPU 1.x (x >= 3) (for network training and evaluation)
• numpy
• scipy
• h5py
• sklearn

License

CC-BY-NC-4.0