Six of us at NYU’s ITP Camp decided to follow The Gloves Project’s patterns to build our own gloves in June. These are sensor-laden gloves that can be used to control software through hand gestures. Our group included musicians, a theatrical sound designer, a gamer, and visualists, each with different uses for the glove in mind.
To get an idea of how it can be used with video in a live setting, take a look at this test clip, where I use hand movement to wirelessly control video playback and effects.
Here, sensor values on the glove are sent via Bluetooth to a decoder patch written in Max, and then out as MIDI controller data to VDMX, VJ software. It works!
Gloves have been used as controllers in live performance for some time — see Laetita Sonami’s Lady’s Glove for example. Our particular design is based on one created for Imogen Heap to use as an Ableton Live controller, so she can get out from behind a computer or keyboard and closer to the audience. She gives a great explanation and demonstration at this Wired Talk (musical performance starts at 13:30).
Heap and The Gloves Project team are into sharing the artistic possibilities of this device with others, as well as increasing the transparency of the musical process which can be obscured inside a computer. This is an attitude I’ve believed in since attending MakerFaire and Blip Festival in 2009, where I saw a range of homemade controllers and instruments. I was much more engaged with the artists who made the causal process visible. It doesn’t have to be all spelled-out, but in certain cases it helps to see the components: the performer is making the things happen. This is obvious with a guitar player, but not so much with electronic music. Also, you get a different creative result by moving your arms than pressing a button — a violin is different from a piano.
The Gloves Project has a residency program where they’ll loan a pair of gloves to artists, plus DIY plans for an Open Source Hardware version. The six of us at ITP Camp built one right-hand glove each. We had to do a bit of deciphering to figure everything out, but we had a range of skills between us and got there in the end.
Each glove has six flex sensors in the fingers (thumb and ring finger have one each, and index and middle have two each, on the upper and lower knuckle), which are essentially resistors: the more they bend, the less electricity passes through. This can be measured and turned into a number. The sensors run to a tiny programmable ArduIMU+ v3 board by DIYDrones, which uses Arduino code and includes a built-in gyroscope, accelerometer, and magnetometer (a compass if you attach a GPS unit for navigation). This is mostly used for flying things like small self-guided airplanes, but also works for motion capture. We make a serial connection to the computer with a wireless bluetooth device.
We had more trouble with the software side of things. The Gloves Project designed is to communicate with their Glover software, written in C++ by Tom Mitchel. There are instructions on the website, but we couldn’t reach anyone to actually get a copy of the program. In the end, we copied the flex sensor sections of Seb Madgwick’s ArduIMU code and used it to modify the ArduIMU v3 code. It delivered a stream of numbers, but we still had to figure out how to turn it into something we could use.
We formatted the output sensor data like this:
Serial.println("THUMB:"); Serial.println(analogRead(A0)); Serial.println("INDEXLOW:"); Serial.println(analogRead(A1)); Serial.println("INDEXUP:"); Serial.println(analogRead(A2));
…and so on. I then programmed a patch in Max to sort it out.
When one of the sensors’ name comes through, Max routes it to a specific switch, opens the switch, lets the next line through (the data for that sensor), and then closes the switch. Data goes where we want, and garbage is ignored.
Every glove and person is slightly different, so next the glove is calibrated. Max looks for the highest and lowest number coming in, and then scales that to the range of a MIDI slider: 0 to 127. When you first start the decoder, you move your hand around as much as you can and voilà! It’s set.
I made the default starting point for flex sensor data 400, since the lowest point sometimes didn’t fall below 0, while the peak was always above 400. The starting point for movement data is 0. There’s also a “slide” object that smooths movement so it doesn’t jump all over the place while still being fairly responsive.
The number is now sent through a Max “send” object with a different name than the raw sensor data. If you’re keeping everything inside Max, you can just set up a corresponding “receive” object.
Otherwise, it gets turned into a MIDI control or note value, and sent out through a local MIDI device or over a network.
Finally, I tidied everything up so it’s useable in presentation mode. Anyone can download the patch and run it in Max Runtime (free).
There are probably more efficient ways of doing this, but it’s our first pass to get things working.
To download all our code, visit https://github.com/timpear/ITP-Gloves/
Since finishing that, I discovered that The Gloves Project has released a whole range of decoders / bridges in various languages. Their ArduIMU code has lots of clever deciphering on the gloves end of things, and the bridges primarily output OSC instead of MIDI, which is handy. Beyond that, The Gloves Project continues to develop new versions of gloves, and are worth checking up on.
Our decoder simply translates the raw sensor data. The next step is to get it to recognize hand gestures, and trigger specific events or adjust values based on that (which is what the Glover software does). We also need to program the glove’s RGB LED and vibration motor for feedback from the computer.
I showed this project to Karl Ward (rock star, Ghost Ghost collaborator, masters student at ITP), and it turns out that he’s currently working on an Arduino library to do a lot of this work, only more elegantly, within the controller. The first library is Filter, which he augmented over the summer to require another new library he wrote, called DataStream. He says: “They are both in usable, tested shape, but the API is still in flux. Right now I’m looking for folks who have Arduino code that does its own filtering, or needs filtering, so I can design the API to fit the most common cases out there.” We’re going to jam.
The glove has all sorts of possible artistic applications, but what else? When I showed it to my dad, he wondered if it could be used as a translator for sign language. Brilliant. It sounds like Microsoft is currently developing software for the Xbox One and new Kinect that will do this, although one advantage of a wearable controller in any case is the ability to get away from a computer (within wireless range). One of the people on our team is going to use it to adjust audio signals while installing sound in theaters. Easier than holding a tablet at the top of a ladder.
Another friend suggested that the glove as demonstrated here could be used for art therapy by people with limited movement. I imagine that something similar is in use out there, but the open-source aspect adds another level of customization and possibility, and again, transparency.
I’m looking to experiment with adjusting specific elements of a video clip with something more organic than a slider or knob, and also be able to interact more directly with a projection. I’ve worked with painter Charlie Kemmerer, creating hybrid painting-projections during Ghost Ghost shows. Charlie works on the canvas with a brush, but even standing beside him, I have to work on an iPad at best. Now I can point directly at the surface while selecting, adjusting, and repositioning clips. Or Charlie could wear it while painting to capture his movement, without it getting in the way of holding a brush.
Creative work reflects the nature of your instrument, so it’s exciting to expand the toolset and learn more about the media. Video A-B fades are pretty straight-forward, but the way that the IMU unit works isn’t nearly as predictable as a fader on a board, and I’ve gotten some unexpected results. That’s a good thing.
Even better, I can’t wait to see what other people with these gloves come up with. Tinker, modify, share.