Blueberry Python SDK

Connect to Blueberry brain sensing pod from Linux, MacOS, RasbperryPi, and Windows.

Install

You should have Python 3.7 or greater installed and the corresponding pip package installed.

Go ahead and git clone this repo (or your fork/copy of it): https://github.com/blueberryxtech/BlueberryPython. Move into the directory you just cloned (cd BlueberryGlassesServer).

Now we need to setup a virtual environment and install dependencies.

Setup and activate virtualenv:

pip3 install virtualenv
python3 -m virtualenv venv
source venv/bin/activate

If in Linux (including Raspberry Pi), run sudo apt-get install libatlas-base-dev.

Install packages:

pip3 install -r requirements.txt

Good to go!

Tested

Ubuntu 20, MacOS, Raspberry Pi 3B+ have been tested to work.

Scripts

Main Example - bby_stream.py

bby_stream.py - connect, see data, and save data to a file - 25 second wait then dies

Blueberry Object - from Blueberry.py import Blueberry

Blueberry.py is the class that allows you to connect and stream data from a blueberry in your own programs.

Blueberry.py contains the class Blueberry which is first instantiated by passing in the device address, parameters, and a callback function. The callback function is run every time new data is received over Bluetooth - this is how your programs can receive data from the Blueberry. Call the run() function of this class to start streaming data. run() is an asyncio asynchronous function so ensure you use asynchronous functions in your own code.

Helper scripts

bby_data_plot.py - plot data created with bby_stream.py
list_devices.py - scan Bluetooth to find your Blueberry
bby_details.py - see information about your Blueberry

Getting Started

List all available Blueberry units (make sure yours is on):

python3 list_bbys.py

Now connect to the unit that you want stream from (this will stream for 25 seconds):

python3 bby_stream.py -a <Blueberry MAC address> -d

Now plot the data:

python3 bby_data_plot.py -f <name of csv file.csv>

Use in your own code

Blueberry.py file has a class Blueberry that is designed to be imported into your project. Just instantiate the class, pass in the device address and a callback, and use the start() function to start connecting and streaming. The callback should accept one dictionary arguement which is structured as follows:

LONG path response:

{'path': 'long_path', 'packet_index': 59, 'channel1': 194, 'channel2': 261, 'channel3': 317, 'sp': 154, 'dp': 55, 'hr': 0, 'hrv': 0, 'ml': 70, 'temperature': 5397}

SHORT path response:

{'path': 'short_path', 'packet_index': 11, 'channel1': 29074, 'channel2': 13263, 'channel3': 76933}

Estimated Metrics (not for medical use, experimental):

DP = diastolic blood pressure SP = systolic blood pressure HR = heart rate HRV = heart rate variability ML = mental_load temperature = body temperature (experimental)

Help

Email cayden at blueberryx.com