Easy way to neuroscience with PiEEG

RaspberryPi to measure and easy study EEG, ECG, EMG, and EOG with Shield PiEEG (sleep, stress control and robot conrol)

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This project was born a few years ago, during a casual conversation over coffee in Tokyo, and has come a long way from just an idea to a prototype in Edinburgh. Now my task is to democratize the field of neuroscience, making it accessible to everyone and I want to do it with PiEEG device, I believe that this will help improve sleep, stress control etc.
At its core, PiEEG is an open-source Raspberry Pi shield that effortlessly measures various biosignals, including electroencephalography (EEG), electromyography (EMG), and ECG. Its versatility, user-friendly interface, and compatibility with diverse electrode types set it apart. With PiEEG, all you need to do is connect the electrodes and run a Python script to start capturing bio-signals.
The potential applications of PiEEG are vast and diverse, ranging from gaming and entertainment to sports, health, and meditation. Additionally, I am currently developing an exclusive neuroscience course centered around PiEEG.

In 2020 I had a dream to control robots via minds, wanted to achieve it, I believed that it can be very useful for people with disability. I tried to find some inexpensive open-source device that is very user-friendly. To my surprise, I did not find a solution that would suit me, it was very strange because as a rule, we can find many shields for different tasks, especially for Arduino or Raspberry Pi, so I decided to quickly make my device in my free time. Unfortunately, all this dragged on for a year, I had no experience in processing EEG data, and for a long time, I could not understand whether my device was working correctly or not. Fortunately, many scientists from the world of neuroscience helped me, and supported me with advice and ideas, as a result In 2021, I developed the initial BCI device called ironbci ( for reading brain signals and extracting valuable correlations for practical purposes.  However, due to the global chip shortage, the production cost of the device skyrocketed. To address this challenge and simplify the installation process, I realized that the best way is to create a shield for a single board computer, that will allow us to measure bio-data. I chose RaspberryPi since it is the most popular single-board computer in the world, and created a device called - PiEEG that allows converting RaspberryPi to a brain-computer interface.   Wherein, In comparison to contemporary EEG systems used across various domains, Raspberry Pi demonstrates superior sampling rates. Utilizing methods that involve direct memory access guarantees the collection of data with utmost precision and stability at the microsecond level. that the best way is to create a shield for single-board computers. 

PiEEG, a breakthrough in BCI technology, offers a cost-effective alternative without compromising on performance. The device's successful presentation at conferences and its recognition in publications (links provided below) attest to its efficacy. To initiate measurements, simply connect PiEEG to a Raspberry Pi and launch our user-friendly software.

Despite the project being open-source, I have received numerous requests from individuals eager to purchase a pre-assembled device rather than building it themselves. Responding to this demand, I have launched a crowdfunding campaign for PiEEG on the reputable platform, Crowd Supply ( ). This campaign aims to make PiEEG accessible to a wider audience while supporting ongoing development and enhancements. Today I am working on implementing a project to control sleep and stress levels on this device, although the potential of the device is much higher

PiEEG offers a seamless and affordable solution for capturing brain signals and unlocking their potential for various applications. Join us in revolutionizing the field of neuroscientific exploration and practical implementation with PiEEG.


Hardware and software manual
EEG hat is very expensive, and costs higher than PiEEG, for this reason, I created a manual on how to create a low-cost EEG hat myself. 
How to connect electrodes and create a hat



Robot toy control via blinking

In the lower graph demonstrated only 1/8 of the upper graph from the right side after The Fast Fourier Transform (FFT)
1. Demonstration - the EEG signal (upper graph) converted to a Fourier series (lower graph). We can see in the lower graph for various frequency ranges, dependence amplitudes from the frequency of blinking (5 Hz and 3 Hz)
2. We set the threshold to the amplitude and connected two diodes. If the amplitude (lower graph) at a frequency of 1-3 Hz becomes more than...

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How to create EEG_hat_DIY.pdf

How connect electrodes and create a hat

Adobe Portable Document Format - 453.09 kB - 03/30/2023 at 13:02


Manual_PiEEG (1).pdf

Software and hardware manual

Adobe Portable Document Format - 356.16 kB - 03/30/2023 at 13:02



How to use it

JPEG Image - 70.23 kB - 03/30/2023 at 10:36


  • 1 × ads1299 Data Converters / Analog to Digital Converter ICs (ADCs)

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