Skip to Content

Open-Source Data Glove

AcceleGlove can be programmed for many applications.

Gloves that are wired with sensors can provide useful information about a user’s motions, and they offer a novel way to interact with computers beyond the keyboard and mouse. At the end of May, AnthroTronix, a company based in Silver Spring, MD, released its first commercial version of the AcceleGlove, a programmable glove that records hand and finger movements. Other gloves–like 5DT’s Data Glove, used primarily in virtual reality–normally cost $1,000 to $5,000, but the AcceleGlove costs just $499. It comes with software that lets developers use Java to program it for any application they wish. AnthroTronix initially developed the glove with the U.S. Department of Defense for robotic control. The glove could also be used in video games, sports training, or physical rehabilitation.

A. Accelerometers
An accelerometer rests just below each fingertip and on the back of the hand. When the user’s hand moves, the accelerometers can detect the three-­dimensional orientation of the fingers and palm with respect to Earth’s gravity. Measured to within a few degrees, this information allows programs to distinguish even very slight changes in hand position.

B. Data Board
The accelerometers feed the position information through lightweight copper wires to a printed circuit board, which sits on the back of the hand. When the user makes a gesture, such as pinching fingers together or holding the open palm outwards, the board transmits the data to a computer through a USB cord plugged in under a flap on top of the glove’s wrist. The glove also receives its power through the cord, avoiding the need for a cumbersome battery pack.

C. Glove
Made of a breathable nylon mix that can stretch to fit hands of different sizes, the glove features open fingertips so a user can type or write while wearing it.

D. Arm Tracker
The glove can track the movement of the user’s arm through an optional component. The arm link consists of two pieces of stretchy fabric, connected by a thin microcontroller, that wrap below the elbow and around the biceps. A potentiometer measures how the elbow flexes, and an accelerometer in the band around the biceps measures the rotation of the arm. The arm link also calculates the location of the wrist with respect to the shoulder, identifies where the wrist is with respect to the rest of the body, and records its movements. This precise measurement allows a user to monitor a football throw or manipulate a robotic arm, for example. The arm tracker plugs in under the same flap in the glove as the USB cord.

Programming
AnthroTronix has created development software that lets users adapt the glove to new purposes. The user builds the glove’s capability by recording a gesture and assigning a meaning to it; the program can store hundreds of gestures. The sensitivity with which the computer recognizes gestures can be varied, so it might recognize sloppy, large gestures for an application such as a children’s educational program, or very precise gestures for robotics. The system can also accept data from two gloves worn simultaneously.

Applications
Users don’t have to tie themselves to the types of gestures that AnthroTronix’s program can understand. While movements of the whole hand through space (such as waving) aren’t recognized by the current software, the glove records raw data that a user could access and analyze using a specialized program such as Mathematica. Users could also write their own software to recognize such gestures, and AnthroTronix plans to release a future version of the developer’s kit that will recognize them.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.