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CTRL-Labs' EEG wristbands may spell the end for keyboards and mice

CTRL-Labs' EEG wristbands may spell the end for keyboards and mice
From Engadget - April 17, 2018

"When your brain wants to go and effect something in these virtual spaces, your brain has to send a signal to your muscle, which has to move your hand, which has to move the device, which has to get picked up by the system, and turned into some sort of action there," Mike Astolfi, head of interactive experiences at CTRL-Labs, explained to Engadget. "And we think we can remove not only the mouse or the controller from that equation, but also, almost your hand from the equation."

The as-of-yet-unnamed device is essentially an EMG wristband. It senses the changes of electrical potential in the user's arm muscles, "the signal that your motor neurons are sending ... the impulses that it's gonna send into the muscles in your arm that will pull on the tendons that connect to your fingers," Astolfi said. This information is then fed back into a machine learning algorithm which enables the system to reconstruct what the hand is doing, whether it's typing, swiping or gesturing.

Measuring the electrical impulses through your arm, rather than your scalp as traditional EEGs do, helps increase signal fidelity. "When you put electrodes on the head, you deal with all the other electrical signals that your brain is putting out. Static from consciousness and seeing, and getting sensations back from the body," Astolfi explained. "When you go down lower to an area like the arm, your body has already done all of the filtering for you." That is, the signals travelling through the arm are those signifying an intentional action, "so it actually gives a lot cleaner signal, and then a lot larger density of signal as we start to drill down into finer grain detecting of the neuron spikes."

A visualization of what the wristbands "see" as the user's hands gesture - image: CTRL-Labs

With a cleaner signal, the system does not have to work as hard to interpret the user's intentions, which in turn helps lower the learning curve needed to acclimate to using it. "You can learn how to do this in 30 seconds to a minute," Astolfi said. Take virtual reality for instance. Most current VR systems (Leap Motion notwithstanding) still rely on handheld controllers to replicate the user's hands in the virtual space. What's more, these controllers only offer between 3 and 6 degrees of freedom, compared to the human hand's 48.

In a VR application, "we are working toward the ability for users to be able to walk up, put the band on, not have to do any training, and be able to roll right away," Astolfi said. "They can start using it using sort of a generalized model."

The wristband would enable users to leverage their hands as in-game controllers as well. "We have the ability to let the user actually customize the signal that they are sending into the device," he continued. "We call it adaptive learning. The idea would be that the device would learn whatever gesture the user's doing, and use that to control something inside of the game."

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