Bramu (Brain music)

Description

Using an consumer-grade EEG device (Muse 2), and Sonic Pi, one can produce interesting sounds.

This repo deals with:

(GUI) connecting the EEG device to a Windows or Ubuntu computer;
(Python) transforming voltages coming from the EEG device to brain waves through FFT;
(Python) computing brain activity metrics;
(Python) sending OSC messages on localhost;
(Python) creating vizualisations
(Sonic Pi) receiving OSC messages and converting them to sounds.

Dependencies

Python 3.7 +

numpy
vispy (advised to install via conda: conda install -c conda-forge vispy)
a backend for vispy (recommended: pyqt, via conda)
pylsl
python-osc
seaborn

Sonic Pi 3.1 +

Contributing

Contributions and collaborations are welcome. For major changes, please open an issue first to discuss what you would like to change.

Acknowledgments

Thanks given to the amazing neuro and Sonic Pi communities.

Thanks to @hyruuk for help connecting the Muse to a laptop with eegsynth.

The core Python code was adapted from https://github.com/alexandrebarachant/muse-lsl/blob/master/examples/neurofeedback.py

Which file should I use ?

You should use muse-windows.py to send OSC.
new-app.py provides visualisation but does not have a calibration time and does not send OSC messages yet.

History

Bramu is an art project derived from an installation done at the Montreal MusicMotion Hacklab 2019, whithin the FundamentalFrequencies team. The installation featured an EEG device (Muse 2), a haptic device (Subpac) and a visual shader that reacts to the participant's brain activity.

Real-time brain activity metrics were derived from the EEG signals using Python and sent in OSC format to the other parts of the installation (samely Sonic-Pi for the haptic and Unity for the shader).

License

MIT

DrAnaximandre/bramu