Real time time frequency plotting of EEG data from the Muse headset.
Project description
Realtime Time-Frequency Visualization
Realtime Time Frequency Plotting of EEG data from Muse headset
https://github.com/dxganta/real-time-tf/assets/47485188/a0484f7d-1aea-43df-84ad-d772f191bb85
Requirements
Compatible with Python 3.x
Compatible with all muse headsets supported by muselsl library
Getting Started
First install muselsl, connect to your muse headset and start a muse stream using
muselsl stream
Then install the realtime_tf package using
pip install real-time-tf
Keep the muselsl stream running and in a separate terminal run
realtime_tf
to visualize the realtime time frequency plot of the streamed eeg data from your muse headset.
The time-frequency plot is shown of 1 second EEG data and the plot is updated every 0.2 seconds by default. But you can update these parameters if required using
realtime_tf --show_time_window NEW_VALUE --update_time_window NEW_VALUE
The muse headset generally has 4 EEG electrodes/channels ('TP9', 'AF7', 'AF8', 'TP10'). By default the time-frequency plot average across all 4 channels is shown. But you can output only the time-frequency plot for a specific channel using
realtime_tf --channel 0
This will output the tf plot for channel 0 which is 'TP9'.
References
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