The new algorithm known as ReFIT can improve the speed and accuracy of neural prosthetics that control computer cursors
Researchers from Stanford University have designed a faster and accurate mathematical algorithm for brain-implantable prosthetic systems which claimed to help disabled people operate computer cursors with their thoughts.
The new algorithm known as ReFIT can improve the speed and accuracy of neural prosthetics that control computer cursors.
ReFIT algorithm system works through a sensor implanted into the brain, which records "action potentials" in neural activity from different electrode sensors and sends data to a computer.
The frequency with which action potentials are generated, it provides input to the computer about the direction and speed of the user’s intended movement.
The system is also claimed to make adjustments swiftly when guiding the cursor to a target, just as a hand and eye would work in tandem to move a mouse-cursor onto an icon on a computer desktop.
Researcher team which designed the system tried to learn from the user’s corrective movements, allowing the cursor to move more precisely to the intended point than it could in earlier prosthetics.
During the trial, the researchers gave tasks to the monkeys for mentally directing a cursor to a target – an onscreen dot – and holding the cursor there for half a second.
ReFIT claimed to better that the previous technology in terms of speed and accuracy, and the cursor reached from the starting point to the target straighter and it reached the target twice as quickly as earlier systems, achieving 75% to 85% of the speed of the monkey’s arm.
The researchers claimed that the efficiency of the algorithm is because of step-by-step calculation that transforms electrical signals from the brain into movements of the cursor onscreen.
The result of the research was published by Stanford University professor electrical engineering, bioengineering and neurobiology Krishna Shenoy and led by research associate Dr. Vikash Gilja and bioengineering doctoral candidate Paul Nuyujukian.
Krishna Shenoy said:"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."