In an early step toward letting severely paralyzed people speak with their thoughts, University of Utah researchers translated brain signals into words using two grids of 16 microelectrodes implanted beneath the skull but atop the brain.
“We have been able to decode spoken words using only signals from the brain with a device that has promise for long-term use in paralyzed patients who cannot now speak,” says Bradley Greger, an assistant professor of bioengineering.
Because the method needs much more improvement and involves placing electrodes on the brain, he expects it will be a few years before clinical trials on paralyzed people who cannot speak due to so-called “locked-in syndrome.”
The Journal of Neural Engineering’s September issue is publishing Greger’s study showing the feasibility of translating brain signals into computer-spoken words.
The University of Utah research team placed grids of tiny microelectrodes over speech centers in the brain of a volunteer with severe epileptic seizures. The man already had a craniotomy – temporary partial skull removal – so doctors could place larger, conventional electrodes to locate the source of his seizures and surgically stop them.
Using the experimental microelectrodes, the scientists recorded brain signals as the patient repeatedly read each of 10 words that might be useful to a paralyzed person: yes, no, hot, cold, hungry, thirsty, hello, goodbye, more and less.
Later, they tried figuring out which brain signals represented each of the 10 words. When they compared any two brain signals – such as those generated when the man said the words “yes” and “no” – they were able to distinguish brain signals for each word 76 percent to 90 percent of the time.
When they examined all 10 brain signal patterns at once, they were able to pick out the correct word any one signal represented only 28 percent to 48 percent of the time – better than chance (which would have been 10 percent) but not good enough for a device to translate a paralyzed person’s thoughts into words spoken by a computer.
“This is proof of concept,” Greger says, “We’ve proven these signals can tell you what the person is saying well above chance. But we need to be able to do more words with more accuracy before it is something a patient really might find useful.”
People who eventually could benefit from a wireless device that converts thoughts into computer-spoken spoken words include those paralyzed by stroke, Lou Gehrig’s disease and trauma, Greger says. People who are now “locked in” often communicate with any movement they can make – blinking an eye or moving a hand slightly – to arduously pick letters or words from a list.
University of Utah colleagues who conducted the study with Greger included electrical engineers Spencer Kellis, a doctoral student, and Richard Brown, dean of the College of Engineering; and Paul House, an assistant professor of neurosurgery. Another coauthor was Kai Miller, a neuroscientist at the University of Washington in Seattle.
Source: Lee J. Siegel
University of Utah