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Iterative Learning Control for Electrical Stimulation and Stroke Rehabilitation (Paperback, 2015 ed.)
Loot Price: R1,961
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Iterative Learning Control for Electrical Stimulation and Stroke Rehabilitation (Paperback, 2015 ed.)
Series: SpringerBriefs in Control, Automation and Robotics
Expected to ship within 10 - 15 working days
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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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