The code can be found here: GitHub - bsl-tools/bsl: A framework for real-time brain signal streaming.
The documentation website can be found here: https://bsl-tools.github.io/
The main features are:
StreamPlayer: creates a mock LSL stream to test scripts/designs
StreamReceiver: connects to one or more LSL streams and retrieves data as numpy array or MNE Raw.
StreamRecorder: connects to one or more LSL streams and record data to disk in
StreamViewer: connects to an LSL stream and visualizes its content in real-time.
BSL is a wrapper around
pylsl simplifying the access to real-time acquisition and visualization of brain signals. For now, it supports only EEG streams, but it is designed to support other brain signals in the future.
BSL is based on NeuroDecode, a library developed by Kyuhwa Lee and improved by Arnaud Desvachez at Campus Biotech Geneva for real-time decoding on EEG signals streamed with LSL.
The original version can be found here:
- GitHub - dbdq/neurodecode: A framework for real-time brain-machine interface
- GitHub - fcbg-hnp/NeuroDecode: A framework for real-time brain-machine interface
BSL drops entirely the decoding capabilities and improves the streaming capabilities of NeuroDecode.
I hope this library will be useful to your research and will help you design and monitor online experiments.