How AI-powered brain implants are helping an ALS patient communicate

What the researchers created is a brain-computer interface —a system that translates neural activity to intended speech—that helps paralyzed individuals, such as those with brainstem strokes or amyotrophic lateral sclerosis , express their thoughts through a computer screen.

“The system has two components. The first is a neural network that decodes phonemes, or units of sound, from neural signals in real-time as the participant is attempting to speak,” says the study’s co-author Erin Michelle Kunz, an electrical engineering PhD student at Stanford University, via email. “The output sequence of phonemes from this network is then passed into a language model which turns it into text of words based on statistics in the English language.

By participating in twice-weekly software training sessions for almost half a year, Bennet was able to have her attempted speech translated at a rate of 62 words a minute, which is faster than previously recorded machine-based speech technology, says Kunz and her team.

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