Easy way to neuroscience with PiEEG for everyone

RaspberryPi to measure and study EEG, ECG, EMG, EOG with PiEEG (sleep, stress control, robot control)
not funded,

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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.

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. 



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 the threshold, then the upper LED will light up.
If the amplitude (lower graph) at a frequency of 3-5 Hz becomes more than the threshold, then the lower LED will light up.
3. Everything is the same, but instead of diodes, we connected output discrete signals to the toy radio control panel and controlled the mouse (ahead, back).

Instead of a toy mouse, you can connect whatever you want.

Everybody can do this device for free himself, all needed sources available on my GitHub

or use my instructions from here

My papers about PiEEG (all papers, all research, and work were made in my free time outside of academic activity, without any financial or other types of support)

1. Rakhmatulin, I., Parfenov, A., Traylor, Z. et al. (2021). Low-cost brain computer interface for everyday use. ExpBrain Res 239, 3573–3583.
2. Rakhmatulin, I. (2021). ironbci - Open-source Brain-computer interface with the embedded board to monitor the physiological subject's condition and environmental parameters arXiv:2111.03656 
3. Rakhmatulin, I . (2021). The electronic board to replace the reference voltage on the earlobe for EEG measurement. March 2021Measurement 173 DOI: 10.1016/j.measurement.2020.108673
4. Rakhmatulin, I. et al. (2021). Raspberry PI Shield - for measure EEG (PIEEG). Conference: 2021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT). DOI: 10.1109/ICEECCOT52851.2021.9707969
5. I Rakhmatulin, S Volkl. (2022). Brain-Computer-Interface controlled robot via RaspberryPi and PiEEG, arXiv preprint arXiv:2202.01936
6. Rakhmatulin, I. (2020). Review of EEG Feature Selection by Neural Networks. Int. J. Sci. Bus. 2020, 4, 101–112.
7. Rakhmatulin, I. (2020). Deep learning and machine learning for EEG signal processing on the example of recognizing the disease of alcoholism.
8. I Rakhmatulin, S Volkl. (2022). PIEEG: Turn a Raspberry Pi into a Brain-Computer-Interface to measure biosignals. arXiv:2201.02228

Media about PiEEG

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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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