“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 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.
The study used a new kind of nonpenetrating microelectrode that sits on the brain without poking into it. These electrodes are known as microECoGs because they are a small version of the much larger electrodes used for electrocorticography, or ECoG, developed a half century ago.
For patients with severe epileptic seizures uncontrolled by medication, surgeons remove part of the skull and place a silicone mat containing ECoG electrodes over the brain for days to weeks while the cranium is held in place but not reattached. The button-sized ECoG electrodes don’t penetrate the brain but detect abnormal electrical activity and allow surgeons to locate and remove a small portion of the brain causing the seizures.
Last year, Greger and colleagues published a study showing the much smaller microECoG electrodes could “read” brain signals controlling arm movements. One of the epileptic patients involved in that study also volunteered for the new study.
Because the microelectrodes do not penetrate brain matter, they are considered safe to place on speech areas of the brain – something that cannot be done with penetrating electrodes that have been used in experimental devices to help paralyzed people control a computer cursor or an artificial arm.
EEG electrodes used on the skull to record brain waves are too big and record too many brain signals to be used easily for decoding speech signals from paralyzed people.
In the new study, the microelectrodes were used to detect weak electrical signals from the brain generated by a few thousand neurons or nerve cells.
MEDICA.de; Source: University of Utah