Yiyue Luo’s Wearable Intelligence Lab at the University of Washington is full of machinery that’s oddly cozy. Here, soft and pliable sensors are sewn, knit and glued directly into clothing to give everyday garments new capabilities.
One of the lab’s newest curiosities is a nondescript gray work glove embedded with sensors that enable it to “feel” on its own. An array of small wires hidden inside the glove report the location and degree of pressure anywhere along its surface. When in use, the signals from the glove inform a realtime “heat map” of pressure that could one day help physical therapy patients track their progress, teach robots to grasp objects, and more.
The OpenTouch Glove project, as it’s officially known, is led by UW electrical and computer engineering doctoral student Devin Murphy as part of a collaboration with the Computational Design and Fabrication Group and Multisensory Intelligence Lab at MIT. UW News caught up with Murphy to learn more about the glove and its potential uses.
What inspired you to create this glove?
Devin Murphy: Our hands are arguably our greatest tools as humans. We interact with the world through our hands in so many different ways. But the nature of how we grasp and manipulate things in our environment is super nuanced and complex, and it’s hard to capture. We have very mature electronics that record sight and sound — think of the cameras and microphones in your smartphone. But there aren’t many electronic devices that record our other senses — like touch. That’s what I’ve been working to remedy with the OpenTouch Glove.
How does the glove work? What are its capabilities?
DM: There are two flexible circuit boards inside each glove that form a grid of wires across the gripping surface of the glove. We can measure pressure at any point in that mesh where two wires meet. The circuit boards connect to a little box of electronics at the user’s wrist, which processes the signals and sends them wirelessly to a laptop.
We can then generate a “heat map” image showing where force is being applied on the hand, where the hand is applying force to different objects and how much force the hand is applying.
This kind of data gives us extra nuance that a camera can’t capture. For example, if your hand is in a bag or behind an object while it’s grasping things, a camera wouldn’t be able to tell what your hand is doing, whereas this glove can follow along.
What are some potential applications for the glove?
DM: I’m particularly excited about how this technology might help patients recovering from an injury. Physical therapists have patients perform a variety of tasks to regain mobility in their hands — if we can measure how much force people apply during this process, we can provide them with concrete feedback. The patient and therapist can both track progress by monitoring grip strength of the patient over time.
We’re also seeing lots of new companies invest in physical intelligence for robotics — basically recording how robots interact with the physical world. If we can record human hand grip signals, we might be able to teach robotic hands how to mimic human behavior.
One other interesting application is in augmented reality or virtual reality. If we replaced traditional controllers with these gloves, it could give users a more natural way to interact with virtual objects and scenery — though we’d need some additional technology for users to feel pressure when gripping virtual things.
How can other researchers access this technology?
DM: It’s really important to us that the glove is accessible to other researchers and anyone else who might want to use it for their own applications. You can order all of the components of the glove directly from commercial manufacturers, and we have released all of the manufacturing files and instructions for putting the glove together yourself.
We’ve also shown some demos of the glove “in the wild” to showcase the different kinds of data it can collect, and we’re planning to release an open source data set collected with the glove in partnership with researchers at MIT.
I’m really excited about developing new wearable technologies that allow people to record less popular sensing modalities like touch. I want to figure out how we can capture the nuances of touch-based interactions, so that ultimately we can get better insights into our daily lives.
For more information, contact Murphy at devinmur@uw.edu.