| This article was prepared by staff writers in collaboration with outside contributors. |
In the field of medical rehabilitation, robots
can act as external aids to assist people in such tasks as lifting a fork
or spoon. But what if robots could be used to retrain the human nervous
system? Many brain-injured patients might one day relearn to perform coordinated
tasks on their own.
Working toward this goal in the Sensory Motor Performance Program at the
Rehabilitation Institute of Chicago is James Patton, a neuroscientist
who combines his medical training with a background in mechanical engineering.
Patton and a team that includes therapists, doctors, and others at the
institute are working with robots in the hope of training people to regain
control over their movements.
The research is funded by the National Institutes of Health, specifically
the National Institute of Child Health and Human Development.
When commands are issued by the nervous system to generate a movement,
they are typically dispatched to several muscles that drive the limb along
the intended path.
It is known that a nervous system possesses the natural capacity to adapt
to environmental forces. For instance, when a force field systematically
disturbs arm motion, people learn to anticipate and compensate for the
force. When the disturbing force field is unexpectedly removed, healthy
subjects make erroneous movements in the opposite direction of the perturbing
force field. This behavior is called an after-effect.
Patton is trying to reverse-engineer this phenomenon to learn the forces
that will result in desirable after-effects. He believes that if he can
custom design a force field to produce a desired trajectory resulting
in an after-effect of adaptation, he would be showing the potential for
neural rehabilitation. Thus, he would be able to use these methods to
teach motor skills to some brain-injured patients.
Using Simulink from The MathWorks in Natick, Mass., Patton starts with
a dynamic simulation of an arm and
the nervous system that controls it. The simulation predicts how people
will respond to a set of forces.
A
MathWorks simulation predicts how a person will react to the force of
a robotic arm. Adaptation could be a key to neural recovery.
Patton has used adaptive training techniques in healthy people to determine
the robot's ability to modify the subjects' hand movements
to a specified trajectory, such as a curved path of some predetermined
shape. And even though the desired after-effect is eventually canceled
out in healthy people, who recognize it as a mistake, Patton believes
that this won't happen in stroke patients, because for them the
after-effect is a healthier movement.
In one preliminary study, Patton asked nine hemiparetic stroke patients
to participate in his adaptive training experiment. The nine patients
were trained by making directed movements in the presence of a force field
specifically designed so that when it was unexpectedly removed, a desired
trajectory would result. The system measured the forces and motions of
each patient's movements.
As Patton explained it, patients would be asked to reach for an object,
but because of their impairment would err in the attempt. By using the
interference of the robot arm, he was essentially "enhancing the
error," so the after-effect would put the patient on target.
Patton said the method differs from that of a therapist, who would attempt
to facilitate movement by showing the patient how to move correctly.
All but one subject showed a significant shift toward the desired trajectory,
even though none of them was given a hint of what it was. Essentially,
the method tricked the nervous system into generating a new motor command.
Although at this time there is no evidence proving that patients can preserve
their after-effects, some patients do appear to preserve limited features
for the duration of the experiment. Patton believes that prolonging the
training over many days could lead to the desired outcome.
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