The first release of the Python Interface has been already a while ago. Time for a new release. What is new?

1. Integrated LSL (lab streaming layer) functionality

LSL has become a well-established tool for the EEG research community to combine different systems. This software solution enables the unified collection of data streams from different sources, adding timestamps to each incoming data point based on a single, shared clock. This means that with LSL you can easily perform hyperscanning (i.e., two or more simultaneous EEG measurement from different participants) and multi-measure studies (i.e., EEG-fNIRS), without having to worry about hardware triggers.

2. Export recordings in .xdf format.

Have more freedom of integrating your recordings into other software programs for analyzing purposes. Using the .xdf file format it is convenient to integrate your data into the MNE-python library, a toolbox tailored to EEG signal analysis. A short example is provided with the interface.

3. HD-EMG activation heatmap

A new type of visualisation has been developed for this release of the Python interface. Aside from signal traces or impedance values, the muscle activation that is recorded with a 32- or 64- channel HD-EMG grid can now be visualised in real-time enabling you to ‘look into’ the muscle’s activation from your screen.

The new release is ready to be downloaded, from December 17, directly from our GitLab page.