Adaptive Spoon Helps Those With Parkinson’s

January 9, 2019 by Bryan Cockfield 6 Comments

There are a lot of side effects of living with medical conditions, and not all of them are obvious. For Parkinson’s disease, one of the conditions is a constant hand tremor. This can obviously lead to frustration with anything that involves fine motor skills, but also includes eating, which can be even more troublesome than other day-to-day tasks. There are some products available that help with the tremors, but at such a high price [Rupin] decided to build a tremor-compensating utensil with off the shelf components instead.

The main source of inspiration for this project was the Liftware Steady, but at around $200 this can be out of reach for a lot of people. The core of this assistive spoon has a bill of material that most of us will have lying around already, in order to keep costs down. It’s built around an Arduino and an MPU6050 inertial measurement unit with two generic servo motors. It did take some 3D printing and a lot of math to get the utensil to behave properly, but the code is available on the project site for anyone who wants to take a look.

This project tackles a problem that we see all the time: a cost-effective, open-source solution to a medical issue where the only alternatives are much more expensive. Usually this comes up around prosthetics, but can also help out by making biological compounds like insulin directly for less than a medical company can provide it.

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Microcontroller And IMU Team Up For Simple Flight Sim Controls

December 23, 2018 by Dan Maloney 3 Comments

Classes are over at Cornell, and that means one thing: the students in [Bruce Land]’s microcontroller design course have submitted their final projects, many of which, like this flight control system for Google Earth’s flight simulator, find their way to the Hackaday tips line.

We actually got this tip several days ago, but since it revealed to us the previously unknown fact that Google Earth has a flight simulator mode, we’ve been somewhat distracted. Normally controlled by mouse and keyboard, [Sheila Balu] decided to give the sim a full set of flight controls to make it more realistic. The controls consist of a joystick with throttle, rudder pedals, and a small control panel with random switches. The whole thing is built of cardboard to keep costs down and to make the system easy to replicate. Interestingly, the joystick does not have the usual gimbals-mounted potentiometers to detect pitch and roll; rather, an IMU mounted on the top of the stick provides data on the stick position. All the controls talk to a PIC32, which sends the inputs over a serial cable to a Python script on the PC running Google Earth; the script simulates the mouse and keyboard commands needed to fly the sim. The video below shows [Sheila] taking an F-16 out for a spin, but despite being a pilot herself since age 16, she was curiously unable to land the fighter jet safely in a suburban neighborhood.

[Bruce]’s course looks like a blast, and [Sheila] clearly enjoyed it. We’re looking forward to the project dump, which last year included this billy-goat balancing Stewart platform, and a robotic ice cream topping applicator.

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Magic Wand Learns Spells Through Machine Learning And An IMU

December 7, 2018 by Al Williams 6 Comments

Jennifer Wang likes to dress up for cosplay and she’s a Harry Potter fan. Her wizarding skills are technological rather than magical but to the casual observer she’s managed to blur those lines. Having a lot of experience with different sensors, she decided to fuse all of this together to make a magic wand. The wand contains an inertial measurement unit (IMU) so it can detect gestures. Instead of hardcoding everything [Jennifer] used machine learning and presented her results at the Hackaday Superconference. Didn’t make it to Supercon? No worries, you can watch her talk on building IMU-based gesture recognition below, and grab the code from GitHub.

Naturally, we enjoyed seeing the technology parts of her project, and this is a great primer on applying machine learning to sensor data. But what we thought was really insightful was the discussions about the entire design lifecycle. Asking questions to scope the design space such as how much money can you spend, who will use the device, and where you will use it are often things we subconsciously answer but don’t make explicit. Failing to answer these questions at all increases the risk your project will fail or, at least, not be as successful as it could have been.

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Looks Like A Glove, Plays Like A Musical Instrument

October 25, 2018 by Donald Papp 8 Comments

The GePS is a musical project that shows how important integration work is when it comes to gesture controls. Creators [Cedric Spindler] and [Frederic Robinson] demonstrate how the output of a hand-mounted IMU (Inertial Measurement Unit) and magnetometer can be used to turn motion, gestures, and quick snap movements into musical output. The GePS is designed to have enough repeatability and low enough latency that feedback is practically immediate. As a result, it can be used and played like any other musical instrument that creates sound from physical movements in a predictable way. It’s not unlike a Theremin in that way, but much more configurable.

To do this, [Cedric] and [Frederic] made GePS from a CurieNano board (based on Intel’s Curie, which also has the IMU on-board) and an XBee radio for a wireless connection to software running on a computer, from which the sounds are played. The device’s sensitivity and low lag means that even small movements can be reliably captured, meaning that the kind of fluid and complex movements that hands do every day can be used as the basis for playing sounds with immediate feedback. In a very real sense, the glove-based GePS is an experimental kind of new instrument, which makes it a fascinating contender for the Musical Instrument Challenge portion of the 2018 Hackaday Prize.

Chordata motion capture dancer and 3D model

A Motion Capture System For Everyone

September 24, 2018 by Steven Dufresne 23 Comments

[Chordata] is making a motion capture system for everyone to build and so far the results are impressive, enough to have been a finalist in the Hackaday Human Computer Interface Challenge. It started a few years ago as one person’s desire to capture a digital performance of a dancer on a stage and has grown into a community of contributors. The board files and software have just been released as alpha along with some instructions for making it work, though more detailed documentation is on the way.

Fifteen sensor boards, called K-Ceptors, are attached to various points on the body, each containing an LSM9DS1 IMU (Inertial Measurement Unit). The K-Ceptors are wired together while still allowing plenty of freedom to move around. Communication is via I2C to a Raspberry Pi. The Pi then sends the collected data over WiFi to a desktop machine. As you move around, a 3D model of a human figure follows in realtime, displayed on the desktop’s screen using Blender, a popular, free 3D modeling software. Of course, you can do something else with the data if you want, perhaps make a robot move? Check out the overview and the performance by a clearly experienced dancer putting the system through its paces in the video below.

As a side note, the latest log entry on their Hackaday.io page points out that whenever changes are made to the K-Ceptor board, fifteen of them need to be made in order to try it out. To help with that, they show the testbed they made for troubleshooting boards as soon as they come out of the oven.

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Using IMUs For Odometry

June 17, 2018 by Brian Benchoff 33 Comments

The future is autonomous robots. Whether that means electric cars with rebranded adaptive cruise control, or delivery robots that are actually just remote control cars, the robots of the future will need to decide how to move, where to move, and be capable of tracking their own movement. This is the problem of odometry, or how far a robot has traveled. There are many ways to solve this problem, but GPS isn’t really accurate enough and putting encoders on wheels doesn’t account for slipping. What’s really needed for robotic odometry is multiple sensors, and for that we have [Pablo] and [Alfonso]’s entry to the Hackaday Prize, the IMcorder.

The IMcorder is a simple device loaded up with an MPU9250 IMU module that has an integrated accelerometer, gyro, and compass. This is attached to an Arduino Pro Mini and a Bluetooth module that allows the IMcorder to communicate with a robot’s main computer to provide information about a robot’s orientation and acceleration. All of this is put together on a fantastically tiny PCB with a lithium battery, allowing this project to be integrated into any robotics project without much, if any, modification.

One interesting aspect of the IMcorders is that they can be used for robot kidnapping issues. This, apparently, is an issue when it comes to robots and other electronic detritus littering the sidewalks. Those electric scooters abandoned on the sidewalk in several cities contain some amazing components that are ripe for some great hardware hacking. Eventually, we’re going to see some news stories about people stealing scooters and delivery robots for their own personal use. Yes, it’s a cyberpunk’s dream, but the IMcorder can be used for a tiny bit of theft prevention. Pity that.

3000W Unicycle’s Only Limitation Is “Personal Courage”

April 23, 2018 by Donald Papp 38 Comments

Electric vehicles are fertile ground for innovation because the availability of suitable motors, controllers, and power sources makes experimentation accessible even to hobbyists. Even so, [John Dingley] has been working on such vehicles since about 2009, and his latest self-balancing electric unicycle really raises the bar by multiple notches. It sports a monstrous 3000 Watt brushless hub motor intended for an electric motorcycle, and [John] was able to add numerous touches such as voice feedback and 1950’s styling using surplus aircraft and motorcycle parts. To steer, the frame changes shape slightly with help of the handlebars to allow the driver’s center of gravity to shift towards one or the other outer rims of the wheel. In a test drive at a deserted beach, [John] tells us that the bike never went above 20% power; the device’s limitations are entirely by personal courage. Watch the video of the test, embedded below.