MNE-Features software for extracting features from multivariate time series
Project description
This repository provides code for feature extraction with M/EEG data. The documentation of the MNE-Features module is available at: documentation.
Installation
To install the package, the simplest way is to use pip to get the latest release:
$ pip install mne-features
Or if you prefer conda:
$ conda install --channel=conda-forge mne-features
Or to get the latest version of the code:
$ pip install git+https://github.com/mne-tools/mne-features.git#egg=mne_features
Dependencies
These are the dependencies to use MNE-Features:
numpy (>=1.17)
matplotlib (>=1.5)
scipy (>=1.0)
numba (>=0.46.0)
llvmlite (>=0.30)
scikit-learn (>=0.21)
mne (>=0.18.2)
PyWavelets (>=0.5.2)
pandas (>=0.25)
Cite
If you use this code in your project, please cite:
Jean-Baptiste SCHIRATTI, Jean-Eudes LE DOUGET, Michel LE VAN QUYEN, Slim ESSID, Alexandre GRAMFORT, "An ensemble learning approach to detect epileptic seizures from long intracranial EEG recordings" Proc. IEEE ICASSP Conf. 2018
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