Stentrodes: A Way To Insert Brain Electrodes Without Invasive Surgery

When we think of brain-computer interfaces (BCIs) that use electrodes, we usually think of Utah arrays that are placed directly on the brain during open brain surgery, or with thin electrodes spliced into the exposed brain as postulated by Neuralink. While Utah arrays and kin as a practical concept date back to the 1980s, a more recent concept called Stentrodes – for stent-electrode array – seeks to do away with the need for invasive brain surgery.

As the name suggests, this approach uses stents that are inserted via the blood vessels, where they are expanded and thus firmly placed inside a blood vessel inside the brain. Since each of these stents also features an electrode array, these can be used to record neural activity in nearby neural clusters, as well as induce activity through electrical stimulation.

Due to the fact that stents are already commonly used by themselves in the brain’s blood vessels, and the relatively benign nature of these electrode arrays, human trials have already been approved in 2018 by an ethics committee in Australia. Despite lingering concerns about the achievable resolution and performance of this approach, it may offer hope to millions of people suffering from paralysis and other conditions.

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3D Printed Prosthesis Reads Your Mind, Sees With Its Hand

Hobbyist electronics and robotics are getting cheaper and easier to build as time moves on, and one advantage of that is the possibility of affordable prosthetics. A great example is this transhumeral prosthesis from [Duy], his entry for this year’s Hackaday Prize.

Side views of the 3D printed prosthesis arm.With ten degrees of freedom, including individual fingers, two axes for the thumb and enough wrist movement for the hand to wave with, this is already a pretty impressive robotics build in and of itself. The features don’t stop there however. The entire prosthesis is modular and can be used in different configurations, and it’s all 3D printed for ease of customization and manufacturing. Along with the myoelectric sensor which is how these prostheses are usually controlled, [Duy] also designed the hand to be controlled with computer vision and brain-controlled interfaces.

The palm of the hand has a camera embedded in it, and by passing that feed through CV software the hand can recognize and track objects the user moves it close to. This makes it easier to grab onto them, since the different gripping patterns required for each object can be programmed into the Raspberry Pi controlling the actuators. Because the alpha-wave BCI may not offer enough discernment for a full range of movement of each finger, this is where computer aid can help the prosthesis feel more natural to the user.

We’ve seen a fair amount of creative custom prostheses here, like this one which uses AI to allow the user to play music with it, and this one which gives its user a tattoo machine for an appendage.

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Brains Controlling Labyrinths Without Hands

[Daniel], [Gal] and [Maxim] attended a hackathon last weekend – Brainihack 2015 – that focused on neuroscience-themed builds in a day and a half long build off. The trio are communications systems engineering and computer science students with no background in neuroscience whatsoever. You can’t build an FMRI in a day and a half, so they ended up winning the best project in the open source category with a brain-controlled labyrinth game.

The labyrinth itself is entirely 3D printed and much, much simpler than the usual, ‘wooden maze with holes’ that’s generally associated with labyrinth puzzles. It’s really just a plastic spiral for a ball to follow. There’s a reason for this simplicity. The team is using EEG to detect brain waves and move the labyrinth on the X and Y axes.

The team is using OpenBCI for the interface between their brains and a pair of servos. This is actually an interesting piece of tech; unlike a few toys like the NeuroSky MindWave and the Star Wars Force Trainer, the OpenBCI gives you eight input channels that attach to anywhere on the scalp. The team used these inputs to measure Alpha waves and Steady State Visually Evoked Potential to control the pair of servos on the labyrinth frame.

It’s a great build, a wonderful demonstration of a device that outputs real EEG signals, and the team on a prize. What’s not to like?