AI-powered brain-computer interface enables ALS patient to communicate and work with 92% accuracy
By
Brandon Vigliarolo
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Summary
A UC Davis research team has developed a machine learning-powered brain-computer interface (BCI) that enables an ALS patient who cannot speak or move to communicate and work a full-time job. The system translates brain activity into sentences with 92% accuracy, allowing the patient to type, browse the web, and perform work tasks. While the hardware itself isn't new, the breakthrough lies in the AI-driven method of decoding neural signals with unprecedented accuracy, giving hope to those with severe paralysis.
Key quotes
· 3 pulledImagine being paralyzed so badly that not only can't you move your hands or feet, but you can't speak either.
For years, brain computer interfaces have presented the tantalizing promise of reading brainwaves well enough to allow a person to communicate and access a PC.
Now, a new breakthrough shows how someone can talk and even work a job while afflicted with a motion-robbing disease.
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