Upper limb stroke rehabilitation: The effectiveness of Stimulation Assistance through Iterative Learning (SAIL)

Abstract

A novel system has been developed which combines robotic therapy with electrical stimulation (ES) for upper limb stroke rehabilitation. This technology, termed SAIL: Stimulation Assistance through Iterative Learning, employs advanced model-based iterative learning control (ILC) algorithms to precisely assist participant's completion of 3D tracking tasks with their impaired arm. Data is reported from a preliminary study with unimpaired participants, and also from a single hemiparetic stroke participant with reduced upper limb function who has used the system in a clinical trial. All participants completed tasks which involved moving their (impaired) arm to follow an image of a slowing moving sphere along a trajectory. The participants' arm was supported by a robot and ES was applied to the triceps brachii and anterior deltoid muscles. During each task, the same tracking trajectory was repeated 6 times and ILC was used to compute the stimulation signals to be applied on the next iteration. Unimpaired participants took part in a single, one hour training session and the stroke participant undertook 18, 1 hour treatment sessions composed of tracking tasks varying in length, orientation and speed. The results reported describe changes in tracking ability and demonstrate feasibility of the SAIL system for upper limb rehabilitation.

DOI: 10.1109/ICORR.2011.5975502

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Cite this paper

@article{Meadmore2011UpperLS, title={Upper limb stroke rehabilitation: The effectiveness of Stimulation Assistance through Iterative Learning (SAIL)}, author={Katie Meadmore and Zhonglun Cai and Daisy Tong and Ann-Marie Hughes and Chris T. Freeman and Eric Rogers and Jane H. Burridge}, journal={2011 IEEE International Conference on Rehabilitation Robotics}, year={2011}, pages={1-6} }