PyEEGLab

Analyze and manipulate EEG data using PyEEGLab.

Introduction

PyEEGLab is a python package developed to define pipeline for EEG preprocessing for a wide range of machine learning tasks. It supports set of datasets out-of-the-box and allow you to adapt your preferred one.

How it Works

Here is a simple quickstart:

from pyeeglab import *
dataset = TUHEEGAbnormalDataset()
preprocessing = Pipeline([
    CommonChannelSet(),
    LowestFrequency(),
    ToDataframe(),
    MinMaxCentralizedNormalization(),
    DynamicWindow(8),
    ToNumpy()
])
dataset = dataset.set_pipeline(preprocessing).load()
data, labels = dataset['data'], dataset['labels']

In this example, for each sample in the dataset, a common set of electrodes is selected, then downsampled to the lowest frequency and normalized using a min-max centralized approach. Each sample is then splitted in eight windows or frames.

This approach is quite usefull for tasks like artifact classification or seizure detection.

How to Install

PyEEGLab is distributed using the pip repository:

pip install PyEEGLab

If you need a bleeding edge version, you can install it directly from GitHub:

pip install git+https://github.com/AlessioZanga/PyEEGLab@develop

Out-Of-The-Box Supported Datasets

The following datasets will work upon downloading:

How to Class Meaning - From the TUH Seizure docs

How to Get a Dataset

WARNING: Retriving the TUH EEG datasets require valid credentials, you can get your own at: https://www.isip.piconepress.com/projects/tuh_eeg/html/request_access.php.

Given the dataset instance, trigger the download using the "download" method:

from pyeeglab import *
dataset = TUHEEGAbnormalDataset()
dataset.download(user='USER', password='PASSWORD')
dataset.index()

then index the new downloaded files.

It should be noted that the download mechanism work on Unix-like systems given the following packages:

sudo apt install sshpass rsync wget

Documentation

WIP: Documentation is currently Work-In-Progress, if you need additional info, please, contact me directly.

You can find the documentation at https://pyeeglab.readthedocs.io

Credits

If you use this code in your project use the citation below:

@misc{Zanga2019PyEEGLab,
    title={PyEEGLab: A simple tool for EEG manipulation},
    author={Alessio Zanga},
    year={2019},
    doi={10.5281/zenodo.3874461},
    url={https://dx.doi.org/10.5281/zenodo.3874461},
    howpublished={\url{https://github.com/AlessioZanga/PyEEGLab}},
}

Related publications

• "An Attention-based Architecture for EEG Classification" - https://doi.org/10.5220/0008953502140219