To Buy - ardEEG is available in the market
Just only 2 script one for Arduino and for Python Python in Windows (etc) and full support from PiEEG))
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.
Warning
You are fully responsible for your personal decision to purchase this device and, ultimately, for its safe use. PiEEG is not a medical device and has not been certified by any government regulatory agency for use with the human body. Use it at your own risk.
Caution
The device must operate only from a battery - 5 V. Complete isolation from the mains power is required.! The device MUST not be connected to any kind of mains power, via USB or otherwise.
Power supply - only battery 5V
It is not a medical device!!! And cannot be used for any medical purposes
Connect the shield to Arduino Uno R4 WiFi and after that connect the device to a battery (power supply) and connect electrodes.
Full galvanic isolation from mains is required.
Electrodes are positioned according to the International 10-20 system
Device Pinout (Shield connected with Arduino Uno R4 only at the next points and power)
Where to use
How connect
In this video you can see how to measure EEG
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The process of measuring chewing and blinking artifacts using dry electrodes (Fz). Chewing occurred in the following sequence: 4 times, 3 times, 2, and 1 time, and the same for the blinking process. The y- axis is the processed EEG signal after passing filter bands of 1-40 Hz in microvolts and with 250 samples per second
Dataset
The process of recording an EEG signal from an electrode (Fz) with eyes open and closed. The y- axis is the processed EEG signal after passing filter bands of 8-12Hz in microvolts and with 250 samples per second
8 channels reading example
Rakhmatulin, I. Low-Cost Shield ardEEG to Measure EEG with Arduino Uno R4 WiFi. Preprints 2024, 2024051643. https://doi.org/10.20944/preprints202405.1643.v1