RESEARCHERS at University of California San Francisco have successfully developed a “speech neuroprosthesis” that has enabled a man with severe paralysis to communicate in sentences, translating signals from his brain to the vocal tract directly into words that appear as text on a screen.

The achievement, which was developed in collaboration with the first participant of a clinical research trial, builds on more than a decade of effort by UCSF neurosurgeon Edward Chang, to develop a technology that allows people with paralysis to communicate even if they are unable to speak on their own. The study appears in the New England Journal of Medicine.

“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 Chang, the Joan and Sanford Weill Chair of Neurological Surgery at UCSF, Jeanne Robertson Distinguished Professor, and senior author on the study. “It shows strong promise to restore communication by tapping into the brain’s natural speech machinery.”

Each year, thousands of people lose the ability to speak due to stroke, accident or disease. With further development, the approach described in this study could one day enable these people to fully communicate.

Previously, work in the field of communication neuroprosthetics has focused on restoring communication through spelling-based approaches to type out letters one-by-one in text. Chang’s study differs from these efforts in a critical way: his team is translating signals intended to control muscles of the vocal system for speaking words, rather than signals to move the arm or hand to enable typing. Chang said this approach taps into the natural and fluid aspects of speech and promises more rapid and organic communication.

“With speech, we normally communicate information at a very high rate, up to 150 or 200 words per minute,” he said, noting that spelling-based approaches using typing, writing, and controlling a cursor are considerably slower and more laborious. “Going straight to words, as we’re doing here, has great advantages because it’s closer to how we normally speak.”

The participant, who asked to be referred to as BRAVO1, worked with the researchers to create a 50-word vocabulary that Chang’s team could recognize from brain activity using advanced computer algorithms. The vocabulary — which includes words such as “water,” “family” and “good” — was sufficient to create hundreds of sentences expressing concepts applicable to BRAVO1’s daily life.

The team found that the system was able to decode words from brain activity at rate of up to 18 words per minute with up to 93 percent accuracy (75 percent median).

The team said they will expand the trial to include more participants affected by severe paralysis and communication deficits. The team is working to increase the number of words in the available vocabulary, as well as improve the rate of speech.(SD-Agencies)