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Stanford Implant Decodes Inner Speech in Real Time With Privacy Passphrase

It demonstrated word decoding rates up to 74 percent with nearly 99 percent detection of a thought-passphrase safeguard.

Overview

  • Stanford researchers implanted microelectrode arrays in the motor cortex of four participants with ALS or post-stroke paralysis to capture neural signals associated with inner speech.
  • The AI-driven system translated these signals into text in real time, recording word accuracy as high as 74 percent in small-vocabulary tests and error rates up to 54 percent with larger word sets.
  • To prevent unintended decoding of spontaneous thoughts, the team added algorithmic filters and required users to think the passphrase “Chitty-Chitty-Bang-Bang,” which was detected nearly 99 percent of the time.
  • Experts warn that the system remains too slow and inconsistent across different tasks and vocabulary sizes and that many spontaneous thoughts may not form clear linguistic sentences.
  • Researchers plan to expand coverage to additional brain regions, boost processing speed and accuracy, and address ethical and regulatory considerations before clinical deployment.