This repository represents the sleep staging classification work down using neural networks at Stanford University, and is intended primarily for research and historical reference.
Those interested in using the sleep staging classification methods that were developed from this should use the primary, Stanford-STAGES repository.
Git provides support for multiple branches of development. Notable branches for this repository include:
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Master (default)
The master branch.
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Historical
The historical branch contains some of the initial sleep staging classification work down using neural networks at Stanford University, and is intended primarily for research and historical reference.
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Dev
The dev branch is the development branch for updating and testing changes to the master branch and is not always stable.
NOTE: Only Python 3.6 and later is supported. Previous versions of Python have been shown to yield erroneous results.
sc_train.py is run by adding an option with the following format:
Example:
python sc_train.py --model ac_lh_ls_lstm
The ac specifies the CC model configuration, the lh specifies the complexity - high in this case, the ls specifies the window length - 15 seconds in this case, and lstm specifies that the model has memory.
To train a model, the sc_config.py should be changed to match the destination for training files, and similarly, to test a model (which has the same option as training) the destination for testing files should be changed.