PiEEG Kit Is A Self-Contained Biosignal Laboratory

Back in 2023, we first brought you word of the PiEEG: a low-cost Raspberry Pi based device designed for detecting and analyzing electroencephalogram (EEG) and other biosignals for the purposes of experimenting with brain-computer interfaces. Developed by [Ildar Rakhmatulin], the hardware has gone through several revisions since then, with this latest incarnation promising to be the most versatile and complete take on the concept yet.

At the core of the project is the PiEEG board itself, which attaches to the Raspberry Pi and allows the single-board computer (SBC) to interface with the necessary electrodes. For safety, the PiEEG and Pi need to remain electrically isolated, so they would have to be powered by a battery. This is no problem while capturing data, as the Pi has enough power to process the incoming signals using the included Python tools, but could be an issue if you wanted to connect the PiEEG system to another computer, say.

For the new PiEEG Kit, the hardware is now enclosed in its own ABS carrying case, which includes an LCD right in the lid. While you’ve still got to provide your own power (such as a USB battery bank), having the on-board display removes the need to connect the Pi to some other system to visualize the data. There’s also a new PCB that allows the connection of additional environmental sensors, breakouts for I2C, SPI, and GPIO, three buttons for user interaction, and an interface for connecting the electrodes that indicates where they should be placed on the body right on the silkscreen.

The crowdsourcing campaign for the PiEEG Kit is set to begin shortly, and the earlier PiEEG-16 hardware is available for purchase currently if you don’t need the fancy new features. Given the fact that the original PiEEG was funded beyond 500% during its campaign in 2023, we imagine there’s going to be plenty of interest in the latest-and-greatest version of this fascinating project.

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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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ArdEEG Lowers The Cost Of Brain-Computer Interfaces

Considering the incredible potential offered by brain-computer interfaces (BCIs), it’s no wonder there are so many companies scrambling to make their mark in the field. Some see it as an assistive technology, while others imagine it as the future of interactive entertainment. Regardless of the application, the technology has yet to make much inroads with the DIY crowd — largely due to the complexity and cost of the hardware involved.

But that might change in the near future thanks to projects like ardEEG from [Ildar Rakhmatulin]. This open source shield mounts to the top of the Arduino UNO R4 WiFi and features eight channels for collecting electroencephalogram (EEG) data, such as from a dry electrode cap. The signals can then be processed on the computer using the provided Python example code. From there, the raw data can be visualized or plugged into whatever application you have in mind.

Why target the relatively uncommon WiFi version of the Uno? It’s probably obvious for those with experience with this kind of hardware, but for safety, the system needs complete electrical isolation. The Arduino and shield are powered by a common USB battery bank, and all communication is done over WiFi. Even still, the documentation is clear that the ardEEG is not a medical device, and hasn’t been certified by any regulatory agency — its use is entirely at your own risk.

[Ildar] tells us the hardware will be available soon and should cost under $250, making it one of the most affordable BCI development platforms out there. As with his earlier PiEEG project, the hope is that basing the system around a common device in the hacker and maker scene will help democratize access to BCI research.

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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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A Sleep Monitor For Minimum Outlay

There are a variety of instruments used in sleep studies to measure bodily activity during sleep and consequent sleep quality. Many of them use techniques that perhaps aren’t so easy to replicate on the bench, but an EEG or electroencephalograph to measure brain waves can be achieved using a readily-available module. [Ben Jabituya] shows us a sleep monitor using one of these modules, an EGG Mikroe Click.

The brains of the operation is an Adafruit Adalogger Feather M0, which is hooked up to a headband containing the sensing electrodes. The write-up gives us a round-up of the available boards, which should be handy for any experimenters in this field. The firmware meanwhile was written using the Arduino IDE. It collects raw sampling data to an SD card, and one surprise comes in just how relatively small a space it requires to store a night’s results.

Finally, a Python script was used to process the data and turn it into a spectrogram to look at brain activity through the night. He envisages using the device for triggering lucid dreaming during REM sleep, but we can see it might be rather useful for sleep disorder sufferers, too. Take a look at it in the video below the break. Continue reading “A Sleep Monitor For Minimum Outlay”

A styrofoam head wearing an electronic headband with cat ears

These Mind-Controlled Cat Ears Move With Your Mood

As any cat owner will tell you, a cat’s ears are great indicators of its state of mind: pointed forward if they want your attention, turned backwards if they’re angry, and folded down flat when they’re afraid. Humans sometimes don cat ear headbands as a fashion statement, but sitting motionless those ears are more likely to confuse a cat than to provide any meaningful communication.

[Jazz DiMauro] aims to fill that gap by designing a cat ear headband that actually responds to your emotions. It does so by continuously taking an EEG measurement and extracting the “attention” and “meditation” variables from it. Those values are then applied to a set of servos that allow two-axis motion on each 3D printed ear. The EEG readout device is an off-the-shelf MindWave headset, which outputs its sensor data through Bluetooth. An Arduino then reads out the data and drives the servos.

Turning all this into a usable wearable device was a project on its own: [Jazz] went through several iterations to find a suitable power source and wiring strategy until they settled on a pair of lithium-polymer batteries and a single flat cable. The end result looks comfortable enough to wear, and the ears’ motion looks smooth and natural. All that’s left is to test it with real cats, to find out if they can now finally understand their human’s emotions too.

We’ve featured a few moving cat ear headbands before: one that moves along with your head’s motions, and another one with manual control. Today’s EEG-powered one shows yet another application for EEGs, which have been used for anything from invoking lucid dreaming to playing beer pong. Continue reading “These Mind-Controlled Cat Ears Move With Your Mood”

The Real Science (Not Armchair Science) Of Consciousness

Among brain researchers there’s a truism that says the reason people underestimate how much unconscious processing goes on in your brain is because you’re not conscious of it. And while there is a lot of unconscious processing, the truism also points out a duality: your brain does both processing that leads to consciousness and processing that does not. As you’ll see below, this duality has opened up a scientific approach to studying consciousness.

Are Subjective Results Scientific?

Researcher checking fMRI images.
Checking fMRI images.

In science we’re used to empirical test results, measurements made in a way that are verifiable, a reading from a calibrated meter where that reading can be made again and again by different people. But what if all you have to go on is what a person says they are experiencing, a subjective observation? That doesn’t sound very scientific.

That lack of non-subjective evidence is a big part of what stalled scientific research into consciousness for many years. But consciousness is unique. While we have measuring tools for observing brain activity, how do you know whether that activity is contributing to a conscious experience or is unconscious? The only way is to ask the person whose brain you’re measuring. Are they conscious of an image being presented to them? If not, then it’s being processed unconsciously. You have to ask them, and their response is, naturally, subjective.

Skepticism about subjective results along with a lack of tools, held back scientific research into consciousness for many years. It was taboo to even use the C-word until the 1980s when researchers decided that subjective results were okay. Since then, here’s been a great deal of scientific research into consciousness and this then is a sampling of that research. And as you’ll see, it’s even saved a life or two.

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