Robotic devices and brain-machine interfaces for hand rehabilitation post-stroke

Alistair C. McConnell, Renan C. Moioli, Fabricio L. Brasil, Marta Vallejo, David W. Corne, Patricia A. Vargas, Adam A. Stokes

Research output: Contribution to journalReview article

14 Citations (Scopus)
39 Downloads (Pure)

Abstract

Objective: To review the state of the art of robotic-aided hand physiotherapy for post-stroke rehabilitation, including the use of brain-machine interfaces. Each patient has a unique clinical history and, in response to personalized treatment needs, research into individualized and at-home treatment options has expanded rapidly in recent years. This has resulted in the development of many devices and design strategies for use in stroke rehabilitation. Methods: The development progression of robotic-aided hand physiotherapy devices and brain-machine interface systems is outlined, focussing on those with mechanisms and control strategies designed to improve recovery outcomes of the hand post-stroke. A total of 110 commercial and non-commercial hand and wrist devices, spanning the 2 major core designs: end-effector and exoskeleton are reviewed. Results: The growing body of evidence on the efficacy and relevance of incorporating brain-machine interfaces in stroke rehabilitation is summarized. The challenges involved in integrating robotic rehabilitation into the healthcare system are discussed. Conclusion: This review provides novel insights into the use of robotics in physiotherapy practice, and may help system designers to develop new devices.

Original languageEnglish
Pages (from-to)449-460
Number of pages12
JournalJournal of Rehabilitation Medicine
Volume49
Issue number6
Early online date8 Jun 2017
DOIs
Publication statusPublished - Jun 2017

Keywords

  • BMI
  • End-effectors
  • Exoskeletons
  • Rehabilitation
  • Stroke

ASJC Scopus subject areas

  • Physical Therapy, Sports Therapy and Rehabilitation
  • Rehabilitation

Fingerprint Dive into the research topics of 'Robotic devices and brain-machine interfaces for hand rehabilitation post-stroke'. Together they form a unique fingerprint.

  • Cite this