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Converting real-time EEG into sounds, music and visual effects

Project description

![](https://github.com/eegsynth/eegsynth/raw/master/doc/figures/EEGsynth_logo.svg?sanitize=true)

The EEGsynth is a [Python](https://www.python.org/) codebase released under the [GNU general public license]( https://en.wikipedia.org/wiki/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). The EEGsynth allows one to use electrical activity recorded from the brain or body to flexibly control devices in real-time, i.e. (re)active and passive brain-computer-interfaces (BCIs), biofeedback and neurofeedback.

Since December 2018, the EEGsynth is registered as a legal _Association_ with the French authorities.

## Documentation

The EEGsynth code and documentation are hosted on Github and organized as follows:

## Disclaimer

The EEGsynth does not allow diagnostic investigations or clinical applications. It also does not provide a graphical user interface for offline analysis. Rather, the EEGsynth is intended as a collaborative interdisciplinary [open-source](https://opensource.com/open-source-way) and [open-hardware](https://opensource.com/resources/what-open-hardware) project that brings together programmers, musicians, artists, neuroscientists and developers in scientific and artistic exploration.

Although there are plans to make it more ‘plug-and-play’, the EEGsynth currently has to be run from the command line, using [Python](https://www.python.org/) and [Bash](https://en.wikipedia.org/wiki/Bash_%28Unix_shell%29) scripts, and is therefor not friendly for those not familiar with such an approach.

## Collaborate and get more information

When you start an project with the EEGsynth, consider doing it together with in a group of people that have knowledge and experience complimentary to yours, such as in electrophysiology, neuroscience, psychology, programming, computer science or signal processing.

More information can be found at [our website](https://www.eegsynth.org). Follow us on [Facebook](https://www.facebook.com/EEGsynth/) and [Twitter](https://twitter.com/eegsynth), and check our past and upcoming events on [our calendar](http://www.eegsynth.org/?calendar=eegsynth-calendar). Please feel free to contact us via our [contact form](http://www.eegsynth.org/?page_id=233).

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