Cleanroom allows you to visualize your brainwaves in a webapp in real-time. Unlike most tools, this avoids lsl. This means fewer dependencies and things that can break. In particular, it's helpful on Raspberry Pi where lsl support (as of August 2018) is iffy. The trade-off is that, unlike lsl, this not battle-tested and should not be used in a production setting.
The UI looks like this, but uhh...bigger:
- A Muse 2016 headset
- If you are on mac or windows, a BLED112 bluetooth LE dongle, as pygatt requires it.
- Plug in the dongle and turn on your Muse headset.
- Clone this repo:
git clone git@github.com:ysimonson/cleanroom.git. - Setup virtualenv:
virtualenv -p python3 venv. - Install dependencies
pip install -r requirements.txt. - Start the server:
python web.py. - Wait for the server to connect to your Muse headset.
- Navigate to
http://localhost:8888.
Mac:
- You may need to manually apply this fix.
Linux:
- If you get an operation not permitted error when starting the server, you need to run this:
sudo setcap 'cap_net_raw,cap_net_admin+eip' `which hcitool`
- Muse LSL
- LSL
- BCI Workshop code, which this repo draws a lot from.