Scientists Convert Brainwaves into Text for Paralyzed Patients

Humans have long been fascinated with the idea of someone or something that can read our minds -- be it a telepath, a computer or Santa Claus. Now scientists say they've developed a system that combines machine learning and a brain-computer interface, or BCI, to read handwriting that takes place in the brain rather than on paper. A team of scientists worked with a 65-year-old man paralyzed from the neck down, using sensors implanted in his brain to detect neural activity linked to writing by hand. As the volunteer imagined writing letters, that activity was fed to an algorithm that translated it, in real time, to text displayed on a screen.

The details of the experiment are laid out in a report in the current issue of the journal Nature. Study co-author Krishna Shenoy, a Howard Hughes Medical Institute investigator at Stanford University, says this method appears to be more potentially powerful than similar studies that have attempted to translate speech rather than handwriting. "Right now, other investigators can achieve about a 50-word dictionary using machine learning methods when decoding speech," Shenoy said in a statement. "By using handwriting to record from hundreds of individual neurons, we can write any letter and thus any word which provides a truly 'open vocabulary' that can be used in most any life situation."



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