From: Stanford University -
11/18/2012
By: Kelly Servick
Stanford University researchers have developed ReFIT, an
algorithm that improves the speed and accuracy of neural prosthetics that
control computer cursors. In a side-by-side comparison, the cursors controlled
by the ReFIT algorithm doubled the performance of existing systems and
approached the performance of a real arm. "These findings could lead to
greatly improved prosthetic system performance and robustness in paralyzed
people, which we are actively pursuing as part of the FDA Phase-I BrainGate2 clinical
trial here at Stanford," says Stanford professor Krishna Shenoy. The
system uses a silicon chip that is implanted in the brain. The chip records
"action potentials" in neural activity from several electrode sensors
and sends the data to a computer. The researchers want to understand how the
system works under closed-loop control conditions in which the computer
analyzes and implements visual feedback taken in real time as the user neurally
controls the cursor toward an onscreen target. The system can make adjustments
in real time while guiding the cursor to a target, similar to how the hand and
eye work in tandem to move a mouse cursor. The researchers designed the
algorithm to learn from the user's corrective movements, allowing the cursor to
move more precisely than in other systems.
Read the entire article and a video (0:25) at:
Links:
Krishna Shenoy
Neural Prosthetic Systems Laboratory
A high-performance neural prosthesis enabled by control
algorithm design http://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.3265.html
Algorithm May Improve Speed and Accuracy of Neural
Prosthetics http://www.rehabpub.com/news/18404-algorithm-may-improve-speed-and-accuracy-of-neural-prosthetics/
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