• Brain-controlled prostheses currently work with access to a sample of only a few hundred neurons, but need to estimate motor commands that involve millions of neurons. So tiny errors in the sample — neurons that fire too fast or too slow — reduce the precision and speed of thought-controlled keypads.

  • The new corrective technique is based on a recently discovered understanding of how monkeys naturally perform arm movements. Shenoy’s team members distilled their understanding of brain dynamics into an algorithm that could analyze the measured electrical signals that their prosthetic device obtained from the sampled neurons. The algorithm tweaked these measured signals so that the sample’s dynamics were more like the baseline brain dynamics. 

  • The goal of all this research is to get thought-controlled prosthetics to people with ALS.The U.S. Food and Drug Administration recently gave Shenoy’s team the green light to conduct a pilot clinical trial of their thought-controlled cursor on people with spinal cord injuries.


Share This Article