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This High School Student Has Created a Device to Help Parkinson's Patients

When Utkarsh Tandon was 10 years old, he saw a YouTube video of Muhammad Ali lighting the Olympic torch. The tremors of the former heavyweight champion sparked his curiosity, and soon, Tandon was reading about Parkinson’s disease. The wheels in his head were already turning on how he could help those who suffered from it.

Fast forward to a few years later when Tandon was in a computer science class, studying machine learning. While researching, he stumbled upon a study in which a phone was secured to the hands of Parkinson’s patients and used to assess their tremors. With that, Tandon was on his way to creating OneRing—a 3-D printed wearable device that was just funded (twice over) on Kickstarter.

Named for the prized ring in J.R.R. Tolkien’s Lord of the Rings, OneRing goes on a patient’s finger and monitors their movements throughout the day. It categorizes those movements based on severity into three categories: dyskinesia, bradykinesia, and tremor. The time-stamped data then appears on an iOS app in the form of a daily report, helping patients and doctors best determine a course of treatment.

The plastic ring contains a box on top that holds a Bluetooth microchip, not unlike other wearable devices like the Fitbit. And like other wearable devices, Tandon is still working on making the design a little more fashion-friendly. He told FastCoDesign: "It has to be something people want to wear. I want to make it look good while it's doing the diagnosis in the background."

OneRing actually started as a 2014 science fair project when Tandon was a high school freshman. He created a machine learning model that did essentially what the product does today—gathers and classifies information on Parkinson’s patients. He won, and received a grant from the UCLA Brain Research Institute, which propelled the development.

Check out OneRing and hear Tandon explain the device in the video above.

[h/t FastCoDesign]

Images via Kickstarter.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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iStock
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Here's How to Change Your Name on Facebook
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iStock

Whether you want to change your legal name, adopt a new nickname, or simply reinvent your online persona, it's helpful to know the process of resetting your name on Facebook. The social media site isn't a fan of fake accounts, and as a result changing your name is a little more complicated than updating your profile picture or relationship status. Luckily, Daily Dot laid out the steps.

Start by going to the blue bar at the top of the page in desktop view and clicking the down arrow to the far right. From here, go to Settings. This should take you to the General Account Settings page. Find your name as it appears on your profile and click the Edit link to the right of it. Now, you can input your preferred first and last name, and if you’d like, your middle name.

The steps are similar in Facebook mobile. To find Settings, tap the More option in the bottom right corner. Go to Account Settings, then General, then hit your name to change it.

Whatever you type should adhere to Facebook's guidelines, which prohibit symbols, numbers, unusual capitalization, and honorifics like Mr., Ms., and Dr. Before landing on a name, make sure you’re ready to commit to it: Facebook won’t let you update it again for 60 days. If you aren’t happy with these restrictions, adding a secondary name or a name pronunciation might better suit your needs. You can do this by going to the Details About You heading under the About page of your profile.

[h/t Daily Dot]

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