Iterative learning control as an enabler for robotic-assisted upper limb stroke rehabilitation

Eric Rogers*, Chris T. Freeman, Ann Marie Hughes, Jane H. Burridge, Katie L. Meadmore, Tim Exell

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

An increased burden on health care and rehabilitation resources is due to the number of people suffering a stroke and if the capacity of health services is to meet future demand novel approaches to rehabilitation are required. In this chapter recent research is surveyed where iterative learning control, developed initially for robots executing commonly encountered industrial tasks such as sequentially collecting objects from one location and transferring them to another, is used to control the assistive stimulation in robotic-assisted upper limb stroke rehabilitation. The results given include the outcomes of small-scale clinical trials with stroke patients and areas for future research are also briefly discussed.

Original languageEnglish
Title of host publicationComplex Systems
Subtitle of host publicationRelationships between Control, Communications and Computing
PublisherSpringer International Publishing AG
Pages157-187
Number of pages31
ISBN (Print)978-3319288604
DOIs
Publication statusPublished - 2016

Publication series

NameStudies in Systems, Decision and Control
PublisherSpringer
Volume55
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190

Fingerprint

Dive into the research topics of 'Iterative learning control as an enabler for robotic-assisted upper limb stroke rehabilitation'. Together they form a unique fingerprint.

Cite this