A Blueprint for Restoring Touch With a Prosthetic Hand
Oct. 14, 2013 — New research
at the University of Chicago is laying the groundwork for
touch-sensitive prosthetic limbs that one day could convey real-time
sensory information to amputees via a direct interface with the brain.
New
research at the University of Chicago is laying the groundwork for
touch-sensitive prosthetic limbs that one day could convey real-time
sensory information to amputees via a direct interface with the brain.
(Credit: PNAS, 2013)
The research, published early online in the Proceedings of the National Academy of Sciences,
marks an important step toward new technology that, if implemented
successfully, would increase the dexterity and clinical viability of
robotic prosthetic limbs.
"To restore sensory motor function of an arm, you not only have to
replace the motor signals that the brain sends to the arm to move it
around, but you also have to replace the sensory signals that the arm
sends back to the brain," said the study's senior author, Sliman
Bensmaia, PhD, assistant professor in the Department of Organismal
Biology and Anatomy at the University of Chicago. "We think the key is
to invoke what we know about how the brain of the intact organism
processes sensory information, and then try to reproduce these patterns
of neural activity through stimulation of the brain."
Bensmaia's research is part of Revolutionizing Prosthetics, a
multi-year Defense Advanced Research Projects Agency (DARPA) project
that seeks to create a modular, artificial upper limb that will restore
natural motor control and sensation in amputees. Managed by the Johns
Hopkins University Applied Physics Laboratory, the project has brought
together an interdisciplinary team of experts from academic
institutions, government agencies and private companies.
Bensmaia and his colleagues at the University of Chicago are working
specifically on the sensory aspects of these limbs. In a series of
experiments with monkeys, whose sensory systems closely resemble those
of humans, they identified patterns of neural activity that occur during
natural object manipulation and then successfully induced these
patterns through artificial means.
The first set of experiments focused on contact location, or sensing
where the skin has been touched. The animals were trained to identify
several patterns of physical contact with their fingers. Researchers
then connected electrodes to areas of the brain corresponding to each
finger and replaced physical touches with electrical stimuli delivered
to the appropriate areas of the brain. The result: The animals responded
the same way to artificial stimulation as they did to physical contact.
Next the researchers focused on the sensation of pressure. In this
case, they developed an algorithm to generate the appropriate amount of
electrical current to elicit a sensation of pressure. Again, the
animals' response was the same whether the stimuli were felt through
their fingers or through artificial means.
Finally, Bensmaia and his colleagues studied the sensation of contact
events. When the hand first touches or releases an object, it produces a
burst of activity in the brain. Again, the researchers established that
these bursts of brain activity can be mimicked through electrical
stimulation.
The result of these experiments is a set of instructions that can be
incorporated into a robotic prosthetic arm to provide sensory feedback
to the brain through a neural interface. Bensmaia believes such feedback
will bring these devices closer to being tested in human clinical
trials.
"The algorithms to decipher motor signals have come quite a long way,
where you can now control arms with seven degrees of freedom. It's very
sophisticated. But I think there's a strong argument to be made that
they will not be clinically viable until the sensory feedback is
incorporated," Bensmaia said. "When it is, the functionality of these
limbs will increase substantially."
The Defense Advanced Research Projects Agency, National Science
Foundation and National Institutes of Health funded this study.
Additional authors include Gregg Tabot, John Dammann, Joshua Berg and
Jessica Boback from the University of Chicago; and Francesco Tenore and
R. Jacob Vogelstein from the Johns Hopkins University Applied Physics
Laboratory.
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