readme.md

OpenBCI Ganglion Node SDK to Lab Streaming Layer

About

This code provides an example of how to stream OpenBCI Ganglion data through the lab streaming layer using the NodeJS SDK.

Follow the steps in this README to start streaming. The code is ready to run as-is, but can be modified and extended to customize how you are sending your data. This is designed to be used with the OpenBCI Ganglion (for Ganglion support, see the Ganglion Node SDK).

Prerequisites

• Python

• ZeroMQ

  pip install pyzmq

• Node.js LTS

• Lab Streaming Layer

   pip install pylsl

Installation

First, install Python dependencies:

python setup.py install

Next, install NodeJS dependencies:

npm install

Note: depending on your computer settings, you may need to run as administrator or with sudo.

Running

npm start

For running just the node, for example if you were running the python in a separate ide and debugging, it's useful.

npm run start-node

Note: depending on your computer settings, you may need to run as administrator or with sudo.

Writing Lab Streaming Layer Code

If you would like to use lab streaming layer in a custom OpenBCI NodeJS application, you must include an instance of the OpenBCI NodeJS library and an instance of a Python interface. A basic example is shown below:

index.js

const Ganglion = require('@openbci/ganglion').Ganglion;
var portPub = 'tcp://127.0.0.1:3004';
var zmq = require('zmq-prebuilt');
var socket = zmq.socket('pair');

let ganglion = new Ganglion();

socket.bind(portPub)

ganglion.once('ganglionFound', (peripheral) => {
  ganglion.searchStop();
  ganglion.on('sample', (sample) => {
    socket.send(JSON.stringify({message: sample}))
  });
  ganglion.once('ready', () => {
    ganglion.streamStart();
  });
  ganglion.connect(peripheral);
});

// ZMQ


/* Insert additional exit handlers and cleanup below*/

handoff.py

import json
import zmq
from pylsl import StreamInfo, StreamOutlet

# Create ZMQ socket
context = zmq.Context()
_socket = context.socket(zmq.PAIR)
_socket.connect("tcp://localhost:3004")

# Create a new labstreaminglayer outlet
numChans = 4;
sampleRate = 256;
info = StreamInfo('OpenBCI_EEG', 'EEG', numChans, sampleRate, 'float32', 'openbci_12345')
outlet = StreamOutlet(info)
# Stream incoming data to LSL
while True:
    msg = _socket.recv()
    try:
      dicty = json.loads(msg)
      message = dicty.get('message')
      data = message.get('channelDataCounts')
      timeStamp = message.get('timeStamp')
      outlet.push_sample(data,timeStamp)
    except BaseException as e:
        print(e)

Contributing

Please PR if you have code to contribute!