The brain is a rather important organ, and as such, nature has gone to great lengths to protect it. The skull provides physical protection against knocks and bumps, but there’s a lesser-known defense mechanism at work too: the blood-brain barrier. It’s responsible for keeping all the nasty stuff – like bacteria, viruses, and weird chemicals – from messing up your head.
Plastic waste is a major problem, but what if you could turn the world’s trash into treasure? [Yayasan Kaki Kita Sukasada (YKKS)] in Indonesia is doing this by using recycled plastic to make prosthetic legs.
Polypropylene source material is shredded and formed into a sheet which is molded into the required shape for the socket. A layer of cloth and foam is used to cushion the interface between the patient and the socket itself. Using waste plastic to make parts for the prosthetics lowers the price for patients as well as helps to keep this material out of the landfill.
What makes this project really exciting is that [YKKS] employs disabled people who develop the prosthetics and also trains patients on how to maintain and repair their prosthetics with easily sourced tools and materials. With some medical device companies abandoning their devices, this is certainly a welcome difference.
Shape shifters have long been the stuff of speculative fiction, but researchers in China have developed a magnetoactive phase transitional matter (MPTM) that makes Odo slipping through an air vent that much more believable.
Soft robots can squeeze into small spaces or change shape as needed, but many of these systems aren’t as strong as their more mechanically rigid siblings. Inspired by the sea cucumber’s ability to manipulate its rigidity, this new MPTM can be inductively heated to a molten state to change shape as well as encapsulate or release materials. The neodymium-iron-boron (NdFeB) microparticles suspended in gallium will then return to solid form once cooled.
Applications in drug delivery, foreign object removal, and smart soldering (video after the break) probably have more real world impact than the LEGO minifig T1000 impersonation, despite how cool that looks. While a pick-and-place can do better soldering work on a factory line, there might be repair situations where a magnetically-controlled solder system could come in handy.
Modern techniques of Coordinated Reset Stimulation (CRS), which is usually administered with invasive deep brain stimulation, can have a miraculous effect on those suffering from Parkinson’s disease. However, the CRS technique can also apparently be administered via so-called vibrotactile CRS (vCRS) which essentially means vibrating certain nerve endings corresponding to brain regions that have a large cortical representation.
An example is vibrating the tips of the fingers using special gloves. This is a medical technique and as such is governed by the FDA. With ongoing trials, patients all around the world will simply have to wait. [HackyDev] has been working with a group of people on developing an open source vCRS glove.
This neuromodulation technique seems so promising, that this upfront effort by hackers around the world is simply a joy to see. Patents be dammed; we can work around them. Interested parties can follow the (very long, tricky-to-follow) thread here.
The hardware [HackyDev] put together uses a nodeMCU as the controller, driving eight motor coils via MOSFETS. The finger-mounted actuators are constructed by ripping the electromagnet out of a relay and mounting it in a 3D printed frame, with a magnet suspended on a spring. This part is mounted on each finger. The nodeMCU presents a simple web form that enables the configuration of the pulse parameters.
A permanent magnet is housed in the spring’s top section
The way the gloves appear to work is due to the way the body perceives sensory input, with a massive bias towards the hands and mouth region, referred to as the cortical homunculus. Each finger has an individual haptic element, which is actuated in a specific sequence with a carefully formed pulse at approx. 250 Hz.
This appears to activate similar in-brain effects as traditional (and invasive) DBS therapy by effectively de-synchronizing certain over-synchronized brain pathways and alleviating the overactive ß-wave activity in the brain. And this calms the tremors as well as many other PD symptoms. It’s all very exciting stuff, and we’ll be following this story closely.
For more on the backstory check out the 2017 paper by Peter A. Tass, as well as this later one, and this one. We’ve seen some recent success with diagnosing or at least detecting PD, by smell as well as via audio, so the future might look a little brighter for quite a number of people.
Prosthetic limb design is an area where desktop manufacturing has made huge strides, but there’s always room for improvement. For example, take a look at [Ian Davis] and his attempts to design a simpler prosthetic finger.
[Davis] favors his aluminum partial hand prosthetic for its strength, but because it was scratch built for his particular situation, it isn’t easy to recreate for someone else. To this end, he has started working on a simpler design that might be applicable in the future for people who want to build their own prosthetics. With less than ten major components per finger including the replaceable TPU fingerpads, this is a major step toward that end.
According to [Davis], one of the more exciting parts of the build is that while this hand has a more limited feature set, he was able to get it closer to the size of his natural hand. Because of the durability problems he’s experienced for day-to-day use of plastic prosthetics, he is having the next iteration 3D printed in stainless steel for further testing.
At the basic level, methods of blood pressure monitoring have slowly changed in the last few decades. While most types of sphygmomanometer still rely on a Velcro cuff placed around the arm, the methodology used in measurement varies. Analog mercury and aneroid types still abound, while digital blood pressure monitors using electrical sensors have become mainstream these days.
One of the challenges of diagnosing diseases is identifying them early. At this stage, signs may be vague or confusing, or difficult to identify. Early diagnosis is often tied to the best possible treatment outcomes, so there’s plenty of incentives to improve methods in this way.
A new voice-based method of diagnosing disease could prove fruitful in this regard. It relies on machine learning techniques to detect when patients may be suffering from certain conditions.
