Software

PiEEG-16 works with two software stacks. Pick the one that fits what you want to do.

PiEEG Server (recommended)

PiEEG Server reads both chips, joins them into one 16-channel stream, filters the signal and serves a browser dashboard plus a real-time data stream. PiEEG-16 is its default device.

# install (first time only)
curl -sSL https://raw.githubusercontent.com/pieeg-club/PiEEG-server/main/install.sh | bash
sudo reboot
 
# run
pieeg-server                   # same as: pieeg-server --device pieeg16

Common options

pieeg-server --filter                       # 1–40 Hz band-pass
pieeg-server --record session.csv           # record while streaming
pieeg-server --lsl                          # Lab Streaming Layer outlet
pieeg-server --osc                          # VRChat OSC bridge
pieeg-server record session.csv --duration 300   # 5-minute CSV, no server
pieeg-server monitor                        # live view in the terminal
pieeg-server doctor                         # check SPI, GPIO and settings

The installer also creates a service that starts the server on every boot. If you run it by hand, stop the service first: sudo systemctl stop pieeg-server.

Read the stream from Python

import asyncio, json, websockets
 
async def main():
    async with websockets.connect("ws://raspberrypi.local:1616") as ws:
        async for msg in ws:
            frame = json.loads(msg)          # {"t": ..., "n": ..., "channels": [16 values in µV]}
            print(frame["n"], frame["channels"])
 
asyncio.run(main())

More: Quick Start · Configuration · WebSocket API · LSL · Recording

Python SDK scripts

Self-contained Python scripts that set up both ADS1299 chips, read raw samples over SPI and plot or save them.

Source: github.com/pieeg-club/PiEEG-16 (opens in a new tab)

Which script

The graph and save scripts use the gpiod==1.5.4 package from PyPI. The command-line recorder uses a different GPIO library (see below). Older versions are kept in the arxive folders.

Install the libraries

Recent Raspberry Pi OS blocks system-wide pip install, so use a virtual environment:

sudo apt install -y python3-venv python3-dev
python3 -m venv --system-site-packages ~/pieeg-env
source ~/pieeg-env/bin/activate
pip install spidev matplotlib scipy pandas openpyxl gpiod==1.5.4

Tested library versions (Python 3.11.2): matplotlib 3.6.3 · spidev 3.5 · scipy 1.10.1 · gpiod 1.5.4

Run

source ~/pieeg-env/bin/activate
git clone https://github.com/pieeg-club/PiEEG-16.git
cd PiEEG-16/GUI
python pieeg16_drdy_only.py

A window opens with the live graphs.

Command-line recorder

pieeg_to_csv.py records straight to CSV without a graph. It uses the system libgpiod bindings and RPi.GPIO rather than gpiod==1.5.4, so give it its own environment:

sudo apt install -y python3-libgpiod
python3 -m venv --system-site-packages ~/pieeg-cli-env
source ~/pieeg-cli-env/bin/activate
pip install spidev numpy RPi.GPIO      # on a Pi 5: pip install spidev numpy rpi-lgpio
 
cd PiEEG-16/Save_data/command_line
python pieeg_to_csv.py --fname session.csv --duration 600 --fs 250 --gain 1

This script reads on a timer rather than on DRDY, and its µV values assume gain 1. For full-rate, DRDY-timed recordings, use pieeg-server record or Save_data_OS.py.

Data tools

The visualisation scripts are not real-time. Set the file path at the top of each script before running it.

Next

• Signals & Datasets: sample recordings and a machine-learning example
• Specification: data frames, registers and µV conversion for writing your own driver