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International Journal of Telemedicine and Applications
Volume 2017, Article ID 2042974, 8 pages
https://doi.org/10.1155/2017/2042974
Research Article

Real-Time Fall Risk Assessment Using Functional Reach Test

1Department of Computer Science and Engineering, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA
2Department of Physical Therapy, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA

Correspondence should be addressed to Mina Sartipi; ude.ctu@ipitras-anim

Received 2 September 2016; Accepted 27 November 2016; Published 10 January 2017

Academic Editor: Malcolm Clarke

Copyright © 2017 Brian Williams et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Falls are common and dangerous for survivors of stroke at all stages of recovery. The widespread need to assess fall risk in real time for individuals after stroke has generated emerging requests for a reliable, inexpensive, quantifiable, and remote clinical measure/tool. In order to meet these requests, we explore the Functional Reach Test (FRT) for real-time fall risk assessment and implement the FRT function in mStroke, a real-time and automatic mobile health system for poststroke recovery and rehabilitation. mStroke is designed, developed, and delivered as an Application (App) running on a hardware platform consisting of an iPad and one or two wireless body motion sensors based on different mobile health functions. The FRT function in mStroke is extensively tested on healthy human subjects to verify its concept and feasibility. Preliminary performance will be presented to justify the further exploration of the FRT function in mStroke through clinical trials on individuals after stroke, which may guide its ubiquitous exploitation in the near future.