US researchers in a world-first have built a neuroprosthetic device that effectively translated the brain waves of a paralyzed man into whole phrases.
The new approach, according to a scientific paper published on Thursday, was designed to facilitate more quick and organic communication, reports the Science Alart.
According to David Moses, postdoctoral engineer at the University of California San Francisco (UCSF) and one of the study's lead authors in the New England Journal of Medicine, "this is an important technological milestone for a person who cannot communicate naturally."
It highlights how this technology has the potential to offer patients with severe paralysis and speech loss a voice, added Moses.
The discovery involves a 36-year-old man who had a stroke when he was 20 and was left with anarthria - the inability to speak clearly despite having normal cognitive function.
Thousands of people lose their ability to speak each year as a result of strokes, accidents, or disease.
Previous research in this field has concentrated on reading brain waves with electrodes in order to construct mobility prosthetics that allow people to spell out letters.
Previously, UCSF researchers used electrode arrays on individuals with normal speech who were undergoing brain surgery to decode the impulses that govern the vocal tract to produce vowels and consonants, and they were able to evaluate the patterns to anticipate words.
But the concept hadn't been tried out on a paralyzed patient to prove it could offer clinical benefit.
Feat of neuroengineering
The team decided to launch a new study called Brain-Computer Interface Restoration of Arm and Voice, and the first participant asked to be referred to as BRAVO1.
Since suffering a devastating brainstem stroke, BRAVO1 has had extremely limited head, neck, and limb movements, and communicates by using a pointer attached to a baseball cap to poke letters on a screen.
The researchers worked with BRAVO1 to develop a 50-word vocabulary with words essential to his daily life like "water," "family," and "good," then surgically implanted a high-density electrode over his speech motor cortex.
Over the next several months, the team recorded his neural activity as he attempted to say the 50 words, and used artificial intelligence to distinguish subtle patterns in the data and tie them to words.
To test it had worked, they presented him with sentences constructed from the vocabulary set, and recorded the results on a screen.
They then prompted him with questions like "How are you today?" and "Would you like some water?" which he was able to answer with responses like, "I am very good," and "No, I am not thirsty."
The system decoded up to 18 words per minute with a median accuracy of 75 percent. An "auto-correct" function, similar to that used in phones, contributed to its success.
"To our knowledge, this is the first successful demonstration of direct decoding of full words from the brain activity of someone who is paralyzed and cannot speak," said BRAVO1's neurosurgeon Edward Chang, a co-author.
An accompanying editorial in the journal hailed the development as "a feat of neuroengineering," and suggested advancements in technology such as smaller surface electrodes might help improve accuracy even further.