Open-Source board for converting RaspberryPI to Brain-computer interface

Overview

The easiest way to the neuroscience world with the shield for RaspberryPi - PIEEG (website). Open-source. Crowdsupply

Software demonstrations

This project is the result of several years of work on the development of BCI. We believe that the easiest way to get started with biosignals is to use a shield. We will try to reveal the process of reading EEG signals as fully and clearly as possible. Soon this project will be launched on the crowdfunding platform - Crowdsupply

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Warning

The device must operate only from a battery - 5 V. Complete isolation from the mains power.! The device MUST not be connected to any kind of mains power, via USB or otherwise

How it Works

1.1.Read_data.c C script for read data in real-time and save to txt file
1.2.Read_data.cpp C++ script for read data in real-time and save to txt file
real_time.py GUI python script for read data in real-time
robot_control.py script to control a robot by blinking

Connect the shield to Raspberry PI 3 or RaspberryPI4 and after that connect the device to a battery (power supply) and connect electrodes. Full galvanic isolation from mains required.
This also applies to the monitor. Use only a monitor that is powered by the RaspberryPI, as in the picture below, left. Electrodes positioned according to International 10-20 system, right.
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Device pinout

Shiled connceted with raspbberryPI only in the netxt points
43 +5V
44 GND
37 MOSI
34 MISO
35 CLKL
36 CS

Noise measure

Chewing artifact (4-3-2-1) and blinking (only 4 times), in real-time for 8 electrodes via real_time.py high-pass filter 1-30 Hz
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Blinking artifact, after Chewing. Raw data alt tag
Raw data with band-pass filter (1-40Hz) alt tag
Alpha wave detection eyes open, eyes closed
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Description of the code

Python script dont allow reading data from ADS1299 with the frequency of 250 Hz. Necessary to use .c or .cpp scripts for reading data in real-time and python for signal processing and vialuzation.

Video - Control robot toy by with blinking

Software demonstrations

For beginners

During the measurement, in addition to artifacts caused by muscle activity, be concerned about the increased resistance between the body and the floor. For example, in the picture below, the moment when the feet touch the floor with and without an insulated shoe. Without insulated shoes - increased noise is noticeable

Citation

Rakhmatulin, I., Volkl, S. (2020). PIEEG: Turn a Raspberry Pi into a Brain-Computer-Interface to measure biosignals. arXiv:2201.02228, https://arxiv.org/abs/2201.02228

Contacts

Crowdsupply
[email protected]
linkedin
Slack - pieeg.slack.com
Web-Site - hackerbci
hackaday blog

Owner
Ildaron
Electronic research engineer. Hardware. Machine Learning.
Ildaron
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