A Personalized Self-Management Rehabilitation System for Stroke Survivors: A Quantitative Gait Analysis Using a Smart Insole.

Davies, R.J. orcid.org/0000-0002-2663-3979, Parker, J. orcid.org/0000-0003-4684-7330, McCullagh, P. orcid.org/0000-0002-9060-6262 et al. (4 more authors) (2016) A Personalized Self-Management Rehabilitation System for Stroke Survivors: A Quantitative Gait Analysis Using a Smart Insole. JMIR Rehabilitation and Assistive Technologies, 3 (2). e11. ISSN 2369-2529

Abstract

Metadata

Authors/Creators:
Copyright, Publisher and Additional Information: ©Richard John Davies, Jack Parker, Paul McCullagh, Huiru Zheng, Chris Nugent, Norman David Black, Susan Mawson. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org), 08.11.2016. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Rehabilitation and Assistive Technology, is properly cited. The complete bibliographic information, a link to the original publication on http://rehab.jmir.org/, as well as this copyright and license information must be included.
Keywords: ambulatory monitoring; gait; rehabilitation; self-management; smart insole; stroke
Dates:
  • Published: 8 November 2016
  • Accepted: 21 August 2016
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > Sheffield Centre for Health and Related Research
The University of Sheffield > Sheffield Teaching Hospitals
Depositing User: Symplectic Sheffield
Date Deposited: 13 Jul 2017 11:39
Last Modified: 13 Jul 2017 11:39
Published Version: https://doi.org/10.2196/rehab.5449
Status: Published
Publisher: JMIR Publications
Refereed: Yes
Identification Number: https://doi.org/10.2196/rehab.5449
Related URLs:

Share / Export

Statistics