Latest PiEEG Shield Now Offers 16 Channels

September 17, 2024 by Tom Nardi 24 Comments

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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Second Human Neuralink Brain Implant Recipient Uses It For CAD And Videogaming

August 22, 2024 by Maya Posch 55 Comments

As Neuralink works towards getting its brain-computer interface technology approved for general use, it now has two human patients who have received the experimental implant. The second patient, [Alex], received the implant in July of 2024 and is said to be doing well, being able to play games like Counter Strike 2 without using his old mouth-operated controller. He’s also creating designs in Fusion 360 to have them 3D printed.

This positive news comes after the first patient ([Noland Arbaugh]) suffered major issues with his implant, with only 10-15% of the electrodes still working after receiving the implant in January. The issue of electrode threads retracting was apparently a known issue years prior already.

We analyzed Neuralink’s claims back in 2019, when its founder – [Elon Musk] – was painting lofty goals for the implant, including reading and writing of brains, integration with AIs and much more. Since that time Neuralink has been mostly in the news for the many test animals which it euthanized during its test campaign prior to embarking on its first human test subjects.

There also appears a continuing issue with transmitting the noisy data from the electrodes, as it is far more data than can be transmitted wirelessly. To solve this seemingly impossible problem, Neuralink has now turned to the public with its Neuralink Compression Challenge to have someone make a miraculous lossless compression algorithm for it.

With still many challenges ahead, it ought to be clear that it will take many more years before Neuralink’s implant is ready for prime-time, but so far at least it seems to at least make life easier for two human patients.

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Brain Implant Uses Graphene Instead Of Metal Probes

July 23, 2024 by Maya Posch 7 Comments

Implantable electrodes for the (human) brain have been around for a many decades in the form of Utah arrays and kin, but these tend to be made out of metal, which can cause issues when stimulating the surrounding neurons with an induced current. This is due to faradaic processes between the metal probe and an electrolyte (i.e. the cerebrospinal fluid). Over time this can result in insulating deposits forming on the probe’s surface, reducing their effectiveness.

Graphene-based, high-resolution cortical brain interface (Credit: Inbrain Neuroelectronics)

Now a company called InBrain claims to have cracked making electrodes out of graphene, following a series of tests on non-human test subjects. Unlike metal probes, these carbon-based probes should be significantly more biocompatible even when used for brain stimulation as with the target goal of treating the symptoms associated with Alzheimer’s.

During the upcoming first phase human subjects would have these implants installed where they would monitor brain activity in Alzheimer’s patients, to gauge how well their medication is helping with the symptoms like tremors. Later these devices would provide deep-brain stimulation, purportedly more efficiently than similar therapies in use today. The FDA was impressed enough at least to give it the ‘breakthrough device’ designation, though it is hard to wade through the marketing hype to get a clear picture of the technology in question.

In their most recently published paper (preprint) in Nature Nanotechnology, [Calia] and colleagues describe flexible graphene depth neural probes (gDNP) which appear to be what is being talked about. These gDNP are used in the experiment to simultaneously record infraslow (<0.1 Hz) and higher frequencies, a feat which metal microelectrodes are claimed to struggle with.

Although few details are available right now, we welcome any brain microelectrode array improvements, as they are incredibly important for many types of medical therapies and research.

ArdEEG Lowers The Cost Of Brain-Computer Interfaces

May 8, 2024 by Tom Nardi 22 Comments

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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Microelectrode (Utay) array and the decoding of the corresponding actions. (Francis R. Willet et al., 2023)

Restoring A Person’s Voice Using A Brain-Computer Interface

August 28, 2023 by Maya Posch 5 Comments

Being able to vocalize is one of the most essential elements of the human experience, with infants expected to start babbling their first words before they’re one year old, and much of their further life revolving around interacting with others using vocalizations involving varying degrees of vocabulary and fluency. This makes the impairment or loss of this ability difficult to devastating, as is the case with locked-in syndrome (LIS), amyotrophic lateral sclerosis (ALS) and similar conditions, where talking and vocalizing has or will become impossible.

In a number of concurrent studies, the use of a brain-computer interface (BCI) is investigated to help patients suffering from LIS (Sean L. Metzger et al., 2023) and ALS (Francis R. Willett et al., 2023) to regain their speaking voice. Using the surgically implanted microelectrode arrays (Utah arrays) electrical impulses pertaining to the patient’s muscles involved in speaking are recorded and mapped to phonemes, which are the elements that make up speech. Each of these phonemes requires a specific configuration of the muscles of the vocal tract (e.g. lips, tongue, jaw and larynx), which can be measured with a fair degree of accuracy. Continue reading “Restoring A Person’s Voice Using A Brain-Computer Interface” →

Noninvasive Sensors For Brain–Machine Interfaces Based On Micropatterned Epitaxial Graphene

April 15, 2023 by Maya Posch 4 Comments

As fun as brain-computer interfaces (BCI) are, for the best results they tend to come with the major asterisk of requiring the cutting and lifting of a section of the skull in order to implant a Utah array or similar electrode system. A non-invasive alternative consists out of electrodes which are placed on the skin, yet at a reduced resolution. These electrodes are the subject of a recent experiment by [Shaikh Nayeem Faisal] and colleagues in ACS Applied NanoMaterials employing graphene-coated electrodes in an attempt to optimize their performance.

Impedance values of eight-channel FEG and eight-channel HPEG sensor systems placed on the occipital area of the head. (Faisal et al., 2023)

Although external electrodes can be acceptable for basic tasks, such as registering a response to a specific (visual) impulse or for EEG recordings, they can be impractical in general use. Much of this is due to the disadvantages of the ‘wet’ and ‘dry’ varieties, which as the name suggests involve an electrically conductive gel with the former.

This gel ensures solid contact and a resistance of no more than 5 – 30 kΩ at 50 Hz, whereas dry sensors perform rather poorly at >200 kΩ at 50 Hz with worse signal-to-noise characteristics, even before adding in issues such as using the sensor on a hairy scalp, as tends to be the case for most human subjects.

In this study, they created electrode arrays in a number of configurations, each of which used graphene as the interface material. The goal was to get a signal even through human hair — such as on the back of the head near the visual cortex — that would be on-par with wet electrodes. The researchers got very promising results with hex-patterned epitaxial graphene (HEPG) sensors, and even in this early prototype stage, the technique could offer an alternative where wet electrodes are not an option.

While the subject is complex, brain-computer interfaces don’t have to be the sole domain of research laboratories. We recently covered an open hardware Raspberry Pi add-on that can let you experiment with detecting and filtering biosignals from the comfort of your own home.

PiEEG Offers Affordable Brain-Computer Interface

April 3, 2023 by Tom Nardi 13 Comments

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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