https://github.com/dominiquemakowski/muselsl2

Light and updated muse-lsl interface to stream and record Muse EEG signals
https://github.com/dominiquemakowski/muselsl2

eeg lsl muse stream

Last synced: about 2 months ago
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Light and updated muse-lsl interface to stream and record Muse EEG signals

• Host: GitHub
• URL: https://github.com/dominiquemakowski/muselsl2
• Owner: DominiqueMakowski
• License: mit
• Created: 2023-09-13T12:20:54.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-01-05T06:51:54.000Z (12 months ago)
• Last Synced: 2024-10-11T18:19:07.846Z (2 months ago)
• Topics: eeg, lsl, muse, stream
• Language: Python
• Homepage:
• Size: 32.8 MB
• Stars: 9
• Watchers: 2
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# MuseLSL2

This is a light reimplementation of [muse-lsl](https://github.com/alexandrebarachant/muse-lsl/) with a few improvements:

- [x] Fixed [timestamps correctness](https://github.com/alexandrebarachant/muse-lsl/pull/197).

- [x] Uses [mne-lsl](https://github.com/mne-tools/mne-lsl), which is an upgraded version of the LSL interface.

- [x] Viewer also shows PPG and related channels.

- [x] Fixed timeout issue and disconnection (to be confirmed)

![](MuseLSL2_viewer.gif)

By default, MuseLSL2 streams *all* channels (including gyroscope, accelerometer, and the signal form the Auxiliary port "AUX", which can be used to add [an additional electrode](https://github.com/andrewjsauer/Muse-EEG-Extra-Electrode-Tutorial)). Note that without an additional electrode, the AUX channel will just pick up noise and should be discarded.

## Usage

Install with:

```

pip install https://github.com/DominiqueMakowski/MuseLSL2/zipball/main

```

Power up Muse EEG headset, Open console, run:

```

MuseLSL2 find

```

Once you have the mac address of your device, run for instance (but replace the address):

```

MuseLSL2 stream --address 00:55:DA:B5:E8:CF

```

In a new console, while streaming, run:

```

MuseLSL2 view

```

## Record

Best is to record the streams using [Lab Recorder](https://github.com/labstreaminglayer/App-LabRecorder).