Provide a stable Python driver for all OpenBCI Biosensors

This repo has been designed to be a more beginner friendly version of the OpenBCI-Python repo. If there is anything you think we should add please open an issue. The OpenBCI-Python repo is still live but it is not longer being mantained by OpenBCI.

Using this repo provides a building block for developing with Python. The goal for the Python library is to provide a stable Python driver for all OpenBCI Biosensors, that:

• Allows Python users to install one module and use any board they choose
• Provides examples of using Python to port data to other apps like lab streaming layer
• Performs the heavy lifting when extracting and transforming raw binary byte streams
• Provides a base for the beginner users to use Python to process their OpenBCI data

• Add Ganglion Aux Data
• Add a script so send commands to the board while streaming.

• Python 2.7 or 3.4+
• Currently the Cyton works on Windows, Linux, and MacOS.
• Ganglion works on Linux only (Linux VM with enabled Bluetooth works as well).
• The WiFi shield is known to have reliability issues across different computer configurations. Using it effectively requires advanced technical skills and programming knowledge. Note that the code avaiable here has not been tested accross all platforms.

First, make sure you have the necessary dependencies.

pip install numpy pyserial bitstring xmltodict requests

Linux users may need bluepy also.

Then you can use pip to install the OpenBCI module.

pip install pyOpenBCI

Once installed, try running the examples provided to make sure you can connect to your OpenBCI board.

Currently the Ganglion board can only be used with a Linux OS. The WiFi shield is known to have reliability issues across different computer configurations. Using it effectively requires advanced technical skills and programming knowledge. Note that the code avaiable here has not been tested accross all platforms.

First you need to initialize your board with one of the following commands:

# For Windows replace '*' with the port number
board = OpenBCICyton(port='COM*')

# For MacOS and Linux replace '*' with the port number
board = OpenBCICyton(port='/dev/ttyUSB*')

To find the COM port you are connected to you can use the OpenBCI GUI. Otherwise you can leave the port number as None, and the function find_port() will run and connect to the first Cyton Dongle it finds.

# For Windows replace '*' with the port number
board = OpenBCICyton(port='COM*', daisy=True)

# For MacOS and Linux replace '*' with the port number
board = OpenBCICyton(port='/dev/ttyUSB*', daisy=True)

To find the COM port you are connected to you can use the OpenBCI GUI. Otherwise you can leave the port number as None, and the function find_port() will run and connect to the first Cyton Dongle it finds.

# For Linux replace '*' with the mac address.
board = OpenBCIGanglion(mac='*')

If you need to find the Ganglion mac address you can use an app like nRF connect to find the ganglion. Otherwise you can leave the mac address as None, and the function find_mac() will run (NOTE: You will need to run the script with sudo for this function to work).

board = OpenBCIWifi(shield_name='OpenBCI-2254', sample_rate=200)

Once you initialize the board you can use the commands on the OpenBCI SDKs (Ganglion, Cyton, Wifi Shield) to send commands to the board using python (make sure your commands are strings).

# Write commands to the board
board.write_command(command)

Here is a table of the most common ones:

To start your stream you can use the following command with a callback function. You can look at the examples folder for some pre-written callback functions.

# Start stream
board.start_stream(callback)

The output of the start_stream function is the OpenBCISample on the callback function. The OpenBCISample object has the following attributes:

• packet_id = The ID of the incomming packet.
• channels_data = The raw EEG data of each channel. 4 for the Ganglion, 8 for the Cyton, and 16 for the Cyton + Daisy.
• aux_data = Accelerometer data.

Because the channels_data and aux_data is the raw data in counts read by the board, we need to multiply the data by a scale factor. There is a specific scale factor for each board:

Multiply uVolts_per_count to convert the channels_data to uVolts.

uVolts_per_count = (4500000)/24/(2**23-1) #uV/count

Multiply accel_G_per_count to convert the aux_data to G.

accel_G_per_count = 0.002 / (2**4) #G/count

Multiply Volts_per_count to convert the channels_data to Volts.

Volts_per_count = 1.2 * 8388607.0 * 1.5 * 51.0 #V/count

Multiply accel_G_per_count to convert the aux_data to G.

accel_G_per_count = 0.032 #G/count

The Wifi Shield already outputs the data in Volts and the aux data in G.

To test this example, use py Examples\print_raw_example.py or python Examples\print_raw_example.py.

from pyOpenBCI import OpenBCICyton

def print_raw(sample):
    print(sample.channels_data)

board = OpenBCICyton(port='COM5', daisy=False)

board.start_stream(print_raw)

To run this example, use py Examples\lsl_example.py or python Examples\lsl_example.py.

from pyOpenBCI import OpenBCICyton
from pylsl import StreamInfo, StreamOutlet
import numpy as np

SCALE_FACTOR_EEG = (4500000)/24/(2**23-1) #uV/count
SCALE_FACTOR_AUX = 0.002 / (2**4)


print("Creating LSL stream for EEG. \nName: OpenBCIEEG\nID: OpenBCItestEEG\n")

info_eeg = StreamInfo('OpenBCIEEG', 'EEG', 8, 250, 'float32', 'OpenBCItestEEG')

print("Creating LSL stream for AUX. \nName: OpenBCIAUX\nID: OpenBCItestEEG\n")

info_aux = StreamInfo('OpenBCIAUX', 'AUX', 3, 250, 'float32', 'OpenBCItestAUX')

outlet_eeg = StreamOutlet(info_eeg)
outlet_aux = StreamOutlet(info_aux)

def lsl_streamers(sample):
    outlet_eeg.push_sample(np.array(sample.channels_data)*SCALE_FACTOR_EEG)
    outlet_aux.push_sample(np.array(sample.aux_data)*SCALE_FACTOR_AUX)

board = OpenBCICyton(port='COM5', daisy=False)

board.start_stream(lsl_streamers)

If you think you can help in any of the areas listed above (and we bet you can) or in any of the many areas that we haven't yet thought of (and here we're sure you can) then please check out our contributors' guidelines and our roadmap.

Please note that it's very important to us that we maintain a positive and supportive environment for everyone who wants to participate. When you join us we ask that you follow our code of conduct in all interactions both on and offline.

If you want to report a problem or suggest an enhancement we'd love for you to open an issue at this github repository because then we can get right on it.

You might be interested in:

• Purchase a Cyton | Ganglion | WiFi Shield from OpenBCI

And of course, you'll want to know our:

• Contributors' guidelines
• Roadmap

OpenBCI boards are commonly referred to as biosensors. A biosensor converts biological data into digital data.

The Ganglion has 4 channels, meaning the Ganglion can take four simultaneous voltage readings.

The Cyton has 8 channels and Cyton with Daisy has 16 channels.

Generally speaking, the Cyton records at a high quality with less noise. Noise is anything that is not signal.

Thank you so much (Danke schön! Merci beaucoup!) for visiting the project and we do hope that you'll join us on this amazing journey to make programming with OpenBCI fun and easy.

MIT