Latest PiEEG Shield Now Offers 16 Channels

We’ve previously covered the PiEEG, an affordable brain-computer interface (BCI) shield designed to connect to the Raspberry Pi. The open source project developed by [Ildar Rakhmatulin] is intended to allow students and hobbyists to experiment with detecting electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG) biosignals — unlocking a wide array of applications ranging from assistive tech to gaming.

Now, the PiEEG hardware has been upgraded to detect sixteen channels via either wet or dry electrodes. The new board, referred to as the PiEEG-16, offers up the same ease of use and features as its predecessor, including the ability to read out signals from the device using Python scripts. Compared to the eight channels supported by the previous generation of hardware, the PiEEG-16 promises to provide the fine-grain data required for more complex operations.

Since we last checked in with the PiEEG back in 2023, [Ildar] says the project has attracted plenty of attention. To help document how the community is using the capability offered by these BCIs, he’s added a page on the project’s site to show off what folks are building with the technology.

Inevitably, some express concern when talking about non-professionals working with brain interfacing hardware. But the project’s documentation is quick to point out that efforts have been taken to make the endeavour as risk-free as possible. The most important thing to remember is that the Raspberry Pi and PiEEG are intended to be powered by batteries so as to remain completely isolated. Similarly, there’s no need to connect the devices to a mains-powered computer, as everything happens on the Pi itself.

Even still, it’s made clear that the PiEEG-16 is not a medical device, and has received no formal certifications. If you want to experiment with this technology, you do so at your own risk. Just something to keep in mind…no pun intended.

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PiEEG Offers Affordable Brain-Computer Interface

One day in the future, we may interact with our electronic devices not with physical input or even voice commands, but simply by thinking about what we want to do. Such brain–computer interfaces (BCIs), combined with machine learning, could allow us to turn our ideas into reality faster and with less effort than ever before — imagine being able to produce a PCB design simply by thinking about how the completed circuit would work. Of course as an assistive technology, BCIs would be nothing less than life-changing for many.

Today BCIs are in their infancy, but that doesn’t mean there isn’t room for hackers and makers to experiment with the concept. [Ildar Rakhmatulin] has been working on low-cost open source BCIs for years, and with the recent release of his PiEEG on Crowd Supply, thinks he’s finally found an affordable solution that will let individuals experiment with this cutting edge technology.

Implemented as a shield that can be connected to a Raspberry Pi 3 or 4, the PiEEG features 8 channels for connecting wet or dry electrodes that can measure biosignals such as those used in electroencephalography (EEG), electromyography (EMG), and electrocardiography (ECG). With the electrodes connected, reading these biosignals is as easy as running a Python script. While primarily designed for neuroscience experimentation, [Ildar] says the device is also useful for learning more about signal processing, filters, and machine learning.

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All About Biosignals

DIY medical science is fun stuff. One can ferret out many of the electrical signals that make the body run with surprisingly accessible components and simple builds. While the medical community predictably dwells on the healthcare uses of such information, the hacker is free to do whatever he or she wants.

A good first start is to look at the relatively strong electrical signals coming off of the heart and other muscles. [Bernd Porr] has put together a simple bioamplifier circuit, and his students have made a series of videos explaining its use that’s well worth your time if you are interested in these things.
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