Abstract
AbstractA nonlinear model-based iterative learning control (ILC) algorithm is applied to the problem of upper limb stroke rehabilitation. A 3D system is developed to assist stroke patients performing 3D upper limb reaching tasks in a virtual reality environment, combining a mechanical support with electrical stimulation applied to two muscles in the patient's arm. ILC is shown to provide accurate trajectory tracking, which maximizes the system's potential to provide effective treatment during future clinical trials. Principal components of the system are described and experimental results confirm its efficacy for use in upper limb stroke rehabilitation.
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