ensemble-eeg 0.1.0

Package used to analyze preprocess edf files for the ENSEMBLE2 study

ENSEMBLE EEG

Ensemble EEG is a library of EEG analyis tools for the ENSEMBLE study. As of today it is focuses on 4 seperate things:

• Anonymizing EDF files in accordance with the ENSEMBLE study and the requirements of EDF+
• Converting BRM to EDF+ files
• Combining seperate aEEG channels into one EDF+ file
• Renaming EEG files according to ENSEMBLE and BIDS standards
• Fixing EDF headers to adhere to the EDF+ standard

Installation

Pip

python3 -m pip install ensemble_eeg

Usage

Anonymizing EDF-files

>>> import ensemble_eeg
>>> ensemble_eeg.anonymize_edf_header('path/2/your/edf/file')

Fixing EDF headers

>>> import ensemble_eeg
>>> ensemble_eeg.fix_edf_header('path/2/your/edf/file')

Converting BRM to EDF files

>>> import brm_to_edf
>>> brm_to_edf.convert_brm_to_edf('path/2/your/brm/file')

Combine left and right aEEG channels into one single file

>>> import ensemble_eeg
>>> ensemble_eeg.combine_aeeg_channels('path/2/your/left/channel', 'path/2/your/right/channel', 'new_filename')

Rename EDF-files according to BIDS and ENSEMBLE standards

>>> import ensemble_eeg
>>> ensemble_eeg.rename_for_ensemble('path/2/your/edf/file')

Situations

1) File is already EDF, but you do not know whether header is EDF+, the file is not anonymized, and not renamed

>>> import ensemble_eeg
>>> file = 'path/2/your/edf/file'
>>> ensemble_eeg.fix_edf_header(file)       # for header check
>>> ensemble_eeg.anonymize_edf_header(file) # for anonymization
>>> ensemble_eeg.rename_for_ensemble(file)  # for renaming

2) File is BRM

>>> import ensemble_eeg
>>> brm_file = 'path/2/your/brm/file'
>>> brm_to_edf.convert_brm_to_edf(brm_file)     # for conversion, output edf is already anonymized
>>> edf_file = 'path/2/your/edf/file'           # check which file was made in previous step
>>> ensemble_eeg.rename_for_ensemble(edf_file)  # for renaming

3) Files are edf, but left and right channel are seperate

>>> import ensemble_eeg
>>> left_file = 'path/2/your/left/edf/file'
>>> right_file = 'path/2/your/right/edf/file'
>>> ensemble_eeg.combine_aeeg_channels(left_file, right_file) # output is automatically anonymized
>>> ensemble_eeg.rename_for_ensemble(file)                    # for renaming

Acknowledgements