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U.S. scientists say they've created algorithms that can help
devices known as brain-machine interfaces to learn as they are
used. Brain machines might someday be used to help paralyzed
patients and amputees control prosthetic limbs with just their
thoughts. University of Florida researchers have devised a way
for the computerized devices to not only translate brain signals
into movement, but also to evolve as the interface learns.
Instead of simply interpreting brain signals and routing them
to a robotic hand or leg in a kind of one-way conversation,
the researchers said the new interface would adapt to a person's
behavior over time and use the knowledge to help complete tasks
more efficiently. "In the grand scheme of brain-machine
interfaces, this is a complete paradigm change," said Assistant
Professor Justin Sanchez, the study's senior author. "This idea
opens up all kinds of possibilities for how we interact with
devices." Sanchez, Professors Jose Principe and Jose Fortes,
and doctoral students Jack DiGiovanna and Babak Mahmoudi report
their research online in the journal IEEE Transactions on
Biomedical Engineering.
devices known as brain-machine interfaces to learn as they are
used. Brain machines might someday be used to help paralyzed
patients and amputees control prosthetic limbs with just their
thoughts. University of Florida researchers have devised a way
for the computerized devices to not only translate brain signals
into movement, but also to evolve as the interface learns.
Instead of simply interpreting brain signals and routing them
to a robotic hand or leg in a kind of one-way conversation,
the researchers said the new interface would adapt to a person's
behavior over time and use the knowledge to help complete tasks
more efficiently. "In the grand scheme of brain-machine
interfaces, this is a complete paradigm change," said Assistant
Professor Justin Sanchez, the study's senior author. "This idea
opens up all kinds of possibilities for how we interact with
devices." Sanchez, Professors Jose Principe and Jose Fortes,
and doctoral students Jack DiGiovanna and Babak Mahmoudi report
their research online in the journal IEEE Transactions on
Biomedical Engineering.