EAN: 9781447167259

SPRINGERBRIEFS IN ELECTRICAL AND COMPUTER ENGIN...

Iterative learning control (ILC) has its origins in the control of processes that perform a
task repetitively with a view to improving accuracy from trial to trial by using information
from previous executions of the task. This brief shows how a classic application of this
technique - trajectory following in robots - can be extended to neurological rehabilitation
after stroke. Regaining upper limb movement is an important step in a return to independence
after stroke  but the prognosis for such recovery has remained poor. Rehabilitation robotics
provides the opportunity for repetitive task-oriented movement practice reflecting the
importance of such intense practice demonstrated by conventional therapeutic research and motor
learning theory. Until now this technique has not allowed feedback from one practice repetition
to influence the next  also implicated as an important factor in therapy. The authors
demonstrate how ILC can be used to adjust external functional electrical stimulation of
patients' muscles while they are repeatedly performing a task in response to the known effects
of stimulation in previous repetitions. As the motor nerves and muscles of the arm reaquire the
ability to convert an intention to move into a motion of accurate trajectory  force and
rapidity  initially intense external stimulation can now be scaled back progressively until the
fullest possible independence of movement is achieved.

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