Brain-Computer Interfaces: Separating Fact From Fiction On Musk’s Brain Implant Claims

July 24, 2019 by Maya Posch 81 Comments

When it comes to something as futuristic-sounding as brain-computer interfaces (BCI), our collective minds tend to zip straight to scenes from countless movies, comics, and other works of science-fiction (including more dystopian scenarios). Our mind’s eye fills with everything from the Borg and neural interfaces of Star Trek, to the neural recording devices with parent-controlled blocking features from Black Mirror, and of course the enslavement of the human race by machines in The Matrix.

And now there’s this Elon Musk guy, proclaiming that he’ll be wiring up people’s brains to computers starting next year, as part of this other company of his: Neuralink. Here the promises and imaginings are truly straight from the realm of sci-fi, ranging from ‘reading and writing’ to the brain, curing brain diseases and merging human minds with artificial intelligence. How much of this is just investor speak? Please join us as we take a look at BCIs, neuroprosthetics and what we can expect of these technologies in the coming years.

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

July 17, 2019 by Erin Pinheiro 4 Comments

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.

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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An Arduino Sickbay Display Worthy Of The Enterprise

July 5, 2019 by Tom Nardi 20 Comments

The various displays and interfaces in Star Trek, especially The Original Series, were intentionally designed to be obtuse and overly complex so they would appear futuristic to the audience. If you can figure out how Sulu was able to fly the Enterprise with an array of unlabeled buttons and rocker switches, we’d love to hear it. But one area of the ship where this abstract design aesthetic was backed off a bit was sickbay, as presumably they wanted the audience to be able to understand at a glance whether or not Kirk or Spock were going to pull through their latest brush with death (spoilers: they’re fine).

For his latest project, [XTronical] has recreated the classic displays from Dr McCoy’s sickbay with an Arduino Nano and a 2.8 inch LCD display. It even has a speaker and MP3 player module to recreate the “heartbeat” sound from the original show. The whole thing looks and sounds phenomenal, and would be a perfect desk toy for the classic Trek aficionado. But this isn’t just a toy, it’s a fully functional medical scanner.

Of course, this little gadget can’t tell you if you’ve come down with a nasty case of Rigellian fever, but it can read your vitals using a MAX30100 pulse oximeter module and DS18B20 thermometer. In fact, it actually has two DS18B20 sensors: one to measure ambient temperature, the other to measure skin temperature. With those two figures, [XTronical] says it can calculate your core body temperature. The only thing that’s made up is the blinking “Respiration” indicator, that one’s just an estimate.

So where do we go from here? This project is presented as merely the first step in building a complete prop, perhaps in the form of a medical tricorder. We’ve seen some phenomenal TOS tricorder builds over the years, and some have even used the Raspberry Pi to shoehorn a bit of functionality into them. [XTronical] says he’s working on getting the source code and a step-by-step build guide put together, so keep an eye out for that in the near future.

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Virtual Reality For Alzheimer’s Detection

May 27, 2019 by Al Williams 10 Comments

You may think of Alzheimer’s as a disease of the elderly, but the truth is people who suffer from it have had it for years — sometimes decades — before they notice. Early detection can help doctors minimize the impact the condition has on your brain, so there’s starting to be an emphasis on testing middle-aged adults for the earliest signs of the illness. It turns out that one of the first noticeable symptoms is a decline in your ability to navigate. [Dennis Chan] at Cambridge Biomedical Research Centre and his team are now using virtual reality to determine how well people can navigate as a way to assess Alzheimer’s earlier than is possible with other techniques.

Current tests mostly measure your ability to remember things, but by the time that’s a problem, things have often progressed. The test has the subject walk to different cones and remember their locations, and has already proven more effective than the standard test.

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Artificial Neural Networks Help Hack Biological Counterparts

May 12, 2019 by Roger Cheng 16 Comments

Eyes are windows into the soul, the old saying goes. They are also pathways into the mind, as much of our brain is involved in processing visual input. This dedication to vision is partly why much of AI research is likewise focused on machine vision. But do artificial neural networks (ANN) actually work like the gray matter that inspired them? A recently published research paper (DOI: 10.1126/science.aav9436) builds a convincing argument for “yes”.

Neural nets were named because their organization was inspired by biological neurons in the brain. But as we learned more and more about how biological neurons worked, we also discovered artificial neurons aren’t very faithful digital copies of the original. This cast doubt whether machine vision neural nets actually function like their natural inspiration, or if they worked in an entirely different way.

This experiment took a trained machine vision network and analyzed its internals. Armed with this knowledge, images were created and tailored for the purpose of triggering high activity in specific neurons. These responses were far stronger than what occurs when processing normal visual input. These tailored images were then shown to three macaque monkeys fitted with electrodes monitoring their neuron activity, which picked up similarly strong neural responses atypical of normal vision.

Manipulating neural activity beyond their normal operating range via tailored imagery is the Hollywood portrayal of mind control, but we’re not at risk of input injection attacks on our brains. This data point gives machine learning researchers confidence their work still has relevance to biological source material, and neuroscientists are excited about the possibility of exploring brain functions without invasive surgical implants. Artificial neural networks could end up help us better understand what happens inside our brain, bringing the process full circle.

[via Science News]

Reverse Engineering An Insulin Pump With An SDR And Decapping

April 29, 2019 by Jenny List 31 Comments

Insulin pumps are a medical device used by people with diabetes to automatically deliver a measured dose of insulin into their bloodstream. Traditionally they have involved a canula and separate connected pump, but more recent models have taken the form of a patch with a pump mounted directly upon it. When [Pete Schwamb]’s daughter received one of these pumps, an Omnipod, he responded to a bounty offer for reverse engineering its RF protocol. As one of the people who helped create Loop, an app framework for controlling insulin delivery systems, he was in a particularly good position to do the work.

The reverse engineering itself started with the familiar tale of using an SDR to eavesdrop on the device’s 433MHz communication between pump and control device. Interrogating the raw data was straightforward enough, but making sense of it was not. There was a problem with the CRC algorithm used by the device which had a bug involving a bitwise shift in the wrong direction, then they hit a brick wall in the encryption of the data. Hardware investigation revealed a custom chip in the device, and there they might have stalled.

But the international reverse engineering community is not without resources and expertise, and through the incredible work of a university researcher in the UK (whose paper incidentally includes a pump teardown) they were able with an arduous process supported by many people to have the firmware recovered through decapping the chip. Even once they had thus extracted the encryption code and produced their own software their problems were not over, because communication issues necessitated a much better antenna on the RileyLink Bluetooth bridge boards that translated Bluetooth from a mobile phone to 433 MHz for the device.

This precis doesn’t fully encapsulate the immense amount of work over several years by a large group of people with some very specialist skills that reverse engineering the Omnipod represents. To succeed in this task is an incredible feat, and makes for a fascinating write-up.

Thanks [Alex] for the tip.

Sound Card ADCs For Electrocardiograms

April 25, 2019 by Brian Benchoff 15 Comments

Every few years, or so we’re told, [Scott] revisits the idea of building an electrocardiogram machine. This is just a small box with three electrodes. Attach them to your chest, and you get a neat readout of your heartbeat. This is a project that has been done to death, but [Scott]’s most recent implementation is fantastic. It’s cheap, relying on the almost absurd capability for analog to digital conversion found in every sound card, and the software is great. It’s the fit and finish that makes this project shine.

The hardware for this build is simply an AD8232, a chip designed to be the front end of any electrocardiogram. This is then simply connected to the microphone port of a sound card through a 1/8″ cable. For the exceptionally clever, there’s a version based on an op-amp. It’s an extraordinarily simple build, but as with all simple builds the real trick is in the software. That’s where this project really shines, with custom software with graphics, and enough information being displayed to actually tell you something.

We’ve seen a number of sound card ADCs being used for electrocardiograms in the past, including some from the Before Times; it makes sense, sound cards are the cheapest way to get a lot of analog data very quickly. You can check out [Scott]’s demo video out below.

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