Skip to main content
Donate to the Python Software Foundation or Purchase a PyCharm License to Benefit the PSF! Donate Now

Stream and visualize EEG data from the Muse headset.

Project description

Muse LSL

A Python package for streaming, visualizing, and recording EEG data from the Muse 2016 headband.

Blinks

Requirements

The code relies on pygatt or BlueMuse for BLE communication and works differently on different operating systems.

  • Windows: On Windows 10, we recommend installing BlueMuse and using its GUI to discover and connect to Muse devices. Alternatively, if you have a BLED112 dongle you can try Muse LSL's bgapi backend (muselsl stream --backend bgapi).
  • Mac: On Mac, a BLED112 dongle is required. The bgapi backend is required and will be used by default when running Muse LSL from the command line
  • Linux: No dongle required. However, you may need to run a command to enable root-level access to bluetooth hardware (see Common Issues). The pygatt backend is required and will be used by default from the command line. and make sure to read the

Compatible with Python 2.7 and Python 3.x

Only compatible with Muse 2 and Muse 2016

Note: if you run into any issues, first check out out Common Issues and then the Issues section of this repository

Getting Started

Installation

Install Muse LSL with pip

pip install muselsl

Setting Up a Stream

On Windows 10, we recommend using the BlueMuse GUI to set up an LSL stream. On Mac and Linux, the easiest way to get Muse data is to use Muse LSL directly from the command line. Use the -h flag to get a comprehensive list of all commands and options.

To print a list of available muses:

$ muselsl list

To begin an LSL stream from the first available Muse:

$ muselsl stream  

To connect to a specific Muse you can pass the name of the device as an argument. Device names can be found on the inside of the left earpiece (e.g. Muse-41D2):

$ muselsl stream --name YOUR_DEVICE_NAME

You can also directly pass the MAC address of your Muse. This provides the benefit of bypassing the device discovery step and can make connecting to devices quicker and more reliable:

$ muselsl stream --address YOUR_DEVICE_ADDRESS

Working with Streaming Data

Once an LSL stream is created, you have access to the following commands.

Note: the process running the stream command must be kept alive in order to maintain the LSL stream. These following commands should be run in another terminal or second process

To view data:

$ muselsl view

If the visualization freezes or is laggy, you can also try the alternate version 2 of the viewer. Note: this will require the additional vispy and mne dependencies

$ muselsl view --version 2

To record EEG data into a CSV:

$ muselsl record --duration 60  

Note: this command will also save data from any LSL stream containing 'Markers' data, such as from the stimulus presentation scripts in EEG Notebooks

Alternatively, you can record data directly without using LSL through the following command:

$ muselsl record_direct --duration 60

Note: direct recording does not allow 'Markers' data to be recorded

Running Experiments

Muse LSL was designed so that the Muse could be used to run a number of classic EEG experiments, including the P300 event-related potential and the SSVEP and SSAEP evoked potentials.

The code to perform these experiments is still available, but is now maintained in the EEG Notebooks repository by the NeuroTechX community.

Usage as a Library

If you want to integrate Muse LSL into your own Python project, you can import and use its functions as you would any Python library. Examples are available in the examples folder:

from muselsl import stream, list_muses

muses = list_muses()
stream(muses[0]['address'])

# Note: Streaming is synchronous, so code here will not execute until after the stream has been closed
print('Stream has ended')

Alternate Data Types

In addition to EEG, the Muse also provides data from an accelerometer, gyroscope, and, in the case of the Muse 2, a photoplethysmography (PPG) sensor. These data types can be enabled via command line arguments or by passing the correct parameters to the stream function. Once enabled, PPG, accelerometer, and gyroscope data will streamed in their own separate LSL streams named "PPG", "ACC", and "GYRO", respectively.

To stream data from all sensors in a Muse 2 from the command line:

muselsl stream --ppg --acc --gyro

As a library function:

from muselsl import stream, list_muses

muses = list_muses()
stream(muses[0]['address'], ppg_enabled=True, acc_enabled=True, gyro_enabled=True)

To record data from an alternate data source:

muselsl record --type ACC

Note: The record process will only record from one data type at a time. However, multiple terminals or processes can be used to record from multiple data types simultaneously

What is LSL?

Lab Streaming Layer or LSL is a system designed to unify the collection of time series data for research experiments. It has become standard in the field of EEG-based brain-computer interfaces for its ability to make seperate streams of data available on a network with time synchronization and near real-time access. For more information, check out this lecture from Modern Brain-Computer Interface Design or the LSL repository

Common Issues

Mac and Windows

  1. Connection issues with BLED112 dongle:
  • You may need to use the --interface argument to provide the appropriate COM port value for the BLED112 device. The default value is COM9. To setup or view the device's COM port go to your OS's system settings

Linux

  1. pygatt.exceptions.BLEError: Unexpected error when scanning: Set scan parameters failed: Operation not permitted (Linux)
  • This is an issue with pygatt requiring root privileges to run a scan. Make sure you have libcap installed and run sudo setcap 'cap_net_raw,cap_net_admin+eip' `which hcitool`
  1. pygatt.exceptions.BLEError: No characteristic found matching 273e0003-4c4d-454d-96be-f03bac821358 (Linux)
  • There is a problem with the most recent version of pygatt. Work around this by downgrading to 3.1.1: pip install pygatt==3.1.1
  1. pygatt.exceptions.BLEError: No BLE adapter found (Linux)
  • Make sure your computer's Bluetooth is turned on.
  1. pygatt.exceptions.BLEError: Unexpected error when scanning: Set scan parameters failed: Connection timed out (Linux)
  • This seems to be due to a OS-level Bluetooth crash. Try turning your computer's bluetooth off and on again
  1. 'RuntimeError: could not create stream outlet' (Linux)
  • This appears to be due to Linux-specific issues with the newest version of pylsl. Ensure that you have pylsl 1.10.5 installed in the environment in which you are trying to run Muse LSL

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
muselsl-2.0.1.tar.gz (116.7 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page