ensemble-eeg 0.1.5

Package used to analyze preprocess edf files for the ENSEMBLE2 study

Table of Contents

1. ENSEMBLE EEG
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Acknowledgments

ENSEMBLE EEG

Ensemble EEG is a library of EEG analyis tools for the ENSEMBLE study. As of today it is focuses on 5 seperate things:

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

Getting started

Prerequisites

The following is required for the use of this software

• Python 3.10 & pip
  • For instructions, please refer to the following link

Installation

python3 -m pip install ensemble_eeg

Usage

Start python

1. From command line
   1. Open cmd / terminal / powershell or your preferred command line interpreter
   2. Type python or python3
2. Using your preferred python interpreter
   1. Jupyter notebook
   2. PyCharm
   3. Spyder

Anonymizing EDF-files

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

Fixing EDF headers

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

Combine left and right aEEG channels into one single file

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

Rename EDF-files according to BIDS and ENSEMBLE standards

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

Example scripts for specific situations

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

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

2) File is .brm

from ensemble_eeg import brm_to_edf
from ensemble_eeg import ensemble_edf
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_edf.rename_for_ensemble(edf_file)  # for renaming

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

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

4) Anonymize multiple .edf files in the same directory

from ensemble_eeg import ensemble_edf
import glob
import os
edf_directory = 'path/2/your/left/edf/directory'
edf_files = glob.glob(os.path.join(edf_directory, "*.edf"))
for file in edf_files:
      ensemble_edf.fix_edf_header(file) 
      ensemble_edf.anonymize_edf_header(file) 
      ensemble_edf.rename_for_ensemble(file)                    

5) Convert multiple .brm files in the same directory

from ensemble_eeg import brm_to_edf
import glob
import os
brm_directory = 'path/2/your/left/edf/directory'
brm_files = glob.glob(os.path.join(brm_directory, "*.brm"))
for file in brm_files:
      brm_to_edf.convert_brm_to_edf(file) 

For more scripts, please refer to the demos folder

Acknowledgements

• edfrd
• Install-Python-Instructions