For an easy-to-use API interfacing with EEG data in EDF, or FIF format in the BIDS-EEG layout. This module stores the code for IO of EEG data for human patients, and pipelining code to convert clinical center data (i.e. time series eeg, clinical metadata) into a developer-friendly dataset that is also invertible and debug-friendly.
- Add support for adding structural context via neuroimaging processed data (e.g. FreeSurfer)
EEGio is intended to be a lightweight wrapper for easily analyzing large batches of patients with EEG data. eegio relies on the following libraries to work:
numpy
scipy
scikit-learn
pandas
mne
mne-bids
pybids
seaborn
matplotlib
pyedflib (deprecated)
xlrd (deprecated)
Epilepsy researchers dealing with EEG data compliant with BIDS and MNE formats. Anyone with human patient EEG data.
See example and docs for info on how to format this.
- https://github.com/bids-standard/bids-specification/blob/master/src/04-modality-specific-files/04-intracranial-electroencephalography.md
- https://github.com/bids-standard/bids-starter-kit/wiki/The-BIDS-folder-hierarchy
These are just lightweight wrappers of MNE/pyedflib reading to load in EDF/FiF data easily, so that raw EEG ts are readily accessible in Python friendly format. We provide an example that was built off of the examples in MNE-BIDS. See example.
For more info, see tutorials and documentation.
We welcome contributions from anyone. Please view our contribution guidelines. Our issues page is a great place for suggestions! If you have an idea for an improvement not listed there, please make an issue first so you can discuss with the developers. For information on setting up testing, see testing guide.
This project is covered under the GNU GPL License.