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The doctors have been able to turn off the brain signals to speech in written sentences, in a research project that aims to transform the way that patients with severe disabilities to communicate.
The breakthrough was said to have been the first to show how the intention to speak of some of the words that can be extracted from brain activity and is rapidly converted to text.
According to The Guardian, the mind-reading software only works with certain phrases that he or she can be trained, although scientists believe that a more robust system could be created in the future.
Doctors at the University of California hopes to have a product that could enable people with paralysis to communicate more easily than existing devices, which will pick up eye movement, and muscle contractions to control a virtual keyboard, a British newspaper reports.
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“At present, there is no voice restoration system, allows the user to view the interactions on the fast time scale of a human conversation,” said Edward Chang, a neurosurgeon and principal investigator of the study.
In three epileptic patients, who were about to get neurosurgery for their condition, had a small patch of electrodes directly on the brain for a week, in order to build up a map of the origins of their seizures, and the researchers in their study.
While in the hospital, the patient reportedly allowed Chang to record their brain activity while they were asked nine questions and asked to read a list of 24 possible responses. Chang’s team built computer models that are consistent with the patterns of brain activity on the questions and the answers.
“This is the first time this approach has been used for the purpose of identifying the spoken words and the phrases,” to David, to Moses, to be a researcher on the team, told The Guardian. “It is important to keep in mind that we have achieved this with a very limited vocabulary, however, in future studies, we hope that we can increase the flexibility and the accuracy of what we will be able to translate it.”
Their findings were published in the journal Nature, the work was funded by Facebook.
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