Brain implant may enable communication from thoughts alone

Scientists have developed a device that can translate a person’s brain signal into what they are traying to say.

The research, published in the Journal Nature Communication was a collaboration between neuroscientists, neurosurgeons and engineers from Duke University's School of Medicine.

"There are many patients who suffer from debilitating motor disorders, like ALS (amyotrophic lateral sclerosis) or locked-in syndrome, that can impair their ability to speak," said Gregory Cogan, Ph.D., a professor of neurology at theUniversity.

"But the current tools available to allow them to communicate are generally very slow and cumbersome."

Imagine listening to an audiobook at half-speed.

That's the best speech decoding rate currently available, which clocks in at about 78 words per minute. People, however, speak around 150 words per minute.

The lag between spoken and decoded speech rates is partially due the relatively few brain activity sensors that can be fused onto a paper-thin piece of material that lays atop the surface of the brain.

Fewer sensors provide less decipherable information to decode.

Overall, the decoder was accurate 40% of the time.

That may seem like a humble test score, but it was quite impressive given that similar brain-to-speech technical feats require hours or days-worth of data to draw from.

The speech decoding algorithm Duraivel used, however, was working with only 90 seconds of spoken data from the 15-minute test.

Duraivel and his mentors are excited about making a cordless version of the device with a recent $2.4M grant from the National Institutes of Health.

"We're now developing the same kind of recording devices, but without any wires," Cogan said.

"You'd be able to move around, and you wouldn't have to be tied to an electrical outlet, which is really exciting."

While their work is encouraging, there's still a long way to go for Viventi and Cogan's speech prosthetic to hit the shelves anytime soon.

"We're at the point where it's still much slower than natural speech," Viventi said in a recent Duke Magazine piece about the technology.

"but you can see the trajectory where you might be able to get there."