minutes of training , and by using a relatively simple decoding algorithm , the device could identify the words with over 90 percent accuracy .
Wandelt presented the study , which is not yet published in a peer-reviewed scientific journal , at the 2022 Society for Neuroscience conference in San Diego . She thinks the findings signify an important proof of concept , though the vocabulary would need to be expanded before a locked-in patient could foil an evil stepmother or procure a glass of water . “ Obviously , the words we chose were not the most informative ones , but if you replace them with yes , no , certain words that are really informative , that would be helpful ,” Wandelt said at the meeting .
“ Spelling things out loud with speech is something that we do pretty commonly , like when you ’ re on the phone with a customer service rep ,” says Sean Metzger , a graduate student in bioengineering at the University of California San Francisco and the University of California , Berkeley . Just like static on a phone line , brain signals can be noisy . Using NATO code words — like Alpha for A , Bravo for B and Charlie for C — makes it easier to discern what someone is saying .
Metzger and his colleagues tested this idea in a participant who was unable to move or speak as the result of a stroke .
The study participant had a larger array of electrodes — about the size of a credit card — implanted over a broad swath of his motor cortex . Rather than eavesdropping on individual neurons , this array records the synchronized activity of tens of thousands of neurons , like hearing an entire section in a football stadium groan or cheer at the same time .
Using this technology , the researchers recorded hours of data and fed it into sophisticated machine learning algorithms . They were able to decode 92 percent of the study subject ’ s silently spelled-out sentences — such as “ That is all right ” or “ What
Thoughts into letters into words
Another approach circumvents the need to build up a big vocabulary by designing a brain-machine interface that recognizes letters instead of words . By trying to mouth out the words that code for each letter of the Roman alphabet , a paralyzed patient could spell out any word that popped into their head , stringing those words together to communicate in full sentences .
VIDEO
This video describes a brain-computer interface under development at UC San Francisco . The team worked with a volunteer who survived a brain stem stroke and can no longer articulate words . An electrode was implanted over an area in the brain that controls the vocal tract . The setup successfully decoded words the volunteer was trying to speak . Read more here .
CREDIT : UC SAN FRANCISCO ( UCSF )
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