Awesome GitHub RepositoriesPython Toolboxes

MNE-Python is an open-source Python library for processing, visualizing, and analyzing human neurophysiological data, including MEG, EEG, sEEG, ECoG, and NIRS recordings. It provides a comprehensive framework for loading data from over 30 proprietary file formats into a common hierarchical FIF data structure, and represents all time-series data as NumPy arrays for seamless integration with the scientific Python ecosystem. The library is built around object-oriented data containers that encapsulate raw, epoched, evoked, and source data with built-in preprocessing and visualization methods. The

scalable analysis of images and time series

pyRiemann is a python package for covariance matrices manipulation and classification through Riemannian geometry.

A toolbox for biosignal processing written in Python.

The EEGsynth is a Python codebase released under the GNU general public license that provides a real-time interface between (open-hardware) devices for electrophysiological recordings (e.g., EEG, EMG and ECG) and analogue and digital devices (e.g., MIDI, lights, games and analogue synthesizers).…

Working with EEG (electroencephalography) data is hard, and this little library aims to make it easier. EEGrunt consists of a collection of functions for reading EEG data from CSV files, converting and filtering it in various ways, and finally generating pretty and informative visualizations.

Wyrm is a Brain Computer Interface (BCI) toolbox written in Python. Wyrm is suitable for running on-line BCI experiments as well as off-line analysis of EEG data.

A Neurofeedback Software for Programmers

A Python package to create real-time Brain Computer Interfaces (BCI's). Data synchronisation and pipelining handled by the Lab Streaming Layer, machine learning with Pytorch, scikit-learn or TensorFlow, leveraging packages like AntroPy, SciPy and NumPy for generic time and/or frequency based…

How to use the FeedbackController

Toolkit and workbench for Brain Computer Interface (BCI) software development, for Python. Modular design built to play well with Machine Learning algorithms that follow python's scikit-learn interface.

Stream 12-channel EEG data from MW75 Neuro headphones with WebSocket, CSV, and LSL output support.

© 2021 nmc-costa. All Rights Reserved. “simplifyhit”™ is a trademark of nmc-costa.

Mother of all BCI Benchmarks Build a comprehensive benchmark of popular Brain-Computer Interface (BCI) algorithms applied on an extensive list of freely available EEG datasets.

Mushu