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Meta-Learning for EEG, Sleep Staging, Transfer Learning, Pre-trained EEG, PSG datasets (IEEE Journal of Biomedical and Health Informatics)

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IoBT-VISTEC/MetaSleepLearner

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N. Banluesombatkul et al., "MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning," in IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2020.3037693.
This source code belongs to INTERFACES (BRAIN lab @ IST, VISTEC, Thailand)

Datasets

Five publicly datasets were used to evaluate our method including

[All of them should be prepared and put in /data - only MASS datasets were pre-processed using bandpass filters as described in our paper]

Algorithm source code (/src)

  • set up configuration i.e. data path, model hyperparameters, etc. in configure.py
  • meta-train (our approach) python MAML.py
  • normal pre-train (baseline) python NormalPretrain.py
  • fine-tune: configure and run python FinetuneCNNKFolds.py
  • evaluate: put list of fine-tune weights path and run notebook FinetuneAndTestOnBestHyperparams-List.ipynb

Other configuration:

  • Every file: set GPU# before running
  • bot.py: add your chat ID and bot token (if you want to have notification, otherwise just remove all lines calling it.)

Citation

To cite our paper,

@ARTICLE{9258375,
  author={N. {Banluesombatkul} and P. {Ouppaphan} and P. {Leelaarporn} and P. {Lakhan} and B. {Chaitusaney} and N. {Jaimchariya} and E. {Chuangsuwanich} and W. {Chen} and H. {Phan} and N. {Dilokthanakul} and T. {Wilaiprasitporn}},
  journal={IEEE Journal of Biomedical and Health Informatics}, 
  title={MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning}, 
  year={2020},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/JBHI.2020.3037693}}

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Meta-Learning for EEG, Sleep Staging, Transfer Learning, Pre-trained EEG, PSG datasets (IEEE Journal of Biomedical and Health Informatics)

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