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A new brain-computer interface (BCI) developed at UC Davis Health translates brain signals into speech with up to 97% accuracy — the most accurate system of its kind. The researchers implanted sensors in the brain of a man with severely impaired speech due to amyotrophic lateral sclerosis (ALS). Casey Harrell was able to communicate his intended speech within minutes of activating the system. A study about this work was published in the New England Journal of Medicine. ALS, also known as Lou Gehrig's disease, affects the nerve cells that control movement throughout the body. The disease leads to a gradual loss of the ability to stand, walk and use one’s hands. It can also cause a person to lose control of the muscles used to speak, leading to a loss of understandable speech. The new technology is being developed to restore communication for people who can’t speak due to paralysis or neurological conditions like ALS. It can interpret brain signals when the user tries to speak and turns them into text that is ‘spoken’ aloud by the computer. The voice was composed using artificial intelligence (AI) trained with existing audio samples of his pre-ALS voice. Read more about this story: UC Davis Neuroprosthetics Lab: BrainGate: See the latest news from UC Davis Health: 0:00 Living with ALS 0:31 BrainGate2 study 1:04 Implanting a BCI for speech 1:51 Using the system for the first time 2:34 Decoding speech using a BCI 3:14 Using AI to reconstruct patient's voice 3:47 Returning to society 4:01 Providing hope for patients #als #braingate #bci #lougehrigsdisease #ucdavis #ai #nejm
