An interdisciplinary team led by Stanford electrical engineer Krishna Shenoy has developed a technique to make brain-controlled prostheses more precise. The prostheses analyze the neuron sample and instantly make dozens of corrective adjustments to the estimate of the brain's electrical pattern.
The team tested a brain-controlled cursor meant to operate a virtual keyboard. The system is intended for people with paralysis and amyotrophic lateral sclerosis (ALS), also called Lou Gehrig's disease.
The new corrective technique is based on a recently discovered understanding of how monkeys naturally perform arm movements. Through hundreds of experiments with monkeys, the researchers learned what the electrical patterns from a 100- to 200-neuron sample looked like during a normal reach.
Shenoy's team members created an algorithm that could analyze the measured electrical signals that their prosthetic device obtained from the sampled neurons. The algorithm tweaked the signals so that the sample's dynamics were more like the baseline brain dynamics.
The new technique continuously corrects brain readings to give people with spinal cord injuries a more precise way to tap out commands by using the thought-controlled cursor. A pilot clinical trial for human use is underway.
