EEG can decode simple thoughts from brainwaves
Stanford University researchers have developed a brain-computer interface that decodes neural signals into text at 62 words per minute, allowing individuals with paralysis to communicate through silent thought with remarkable precision.
A high-bandwidth brain-computer interface can now decode internal speech into text at speeds approaching natural conversation. In a 2023 study led by Stanford University neuroscientist Francis Willett, researchers utilized implanted electrode arrays to monitor neural activity in a patient with amyotrophic lateral sclerosis. The system translated the patient's intended speech into text at a rate of 62 words per minute, which is over three times faster than previous records.
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