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Information 2016, 7(3), 47; doi:10.3390/info7030047

An mHealth Tool Suite for Mobility Assessment

Electrical and Computer Engineering Department, The University of Alabama in Huntsville, Huntsville, AL 35899, USA
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Academic Editors: Jack Bobak Mortazavi, Hassan Ghasemzadeh, Sunghoon Ivan Lee and Nabil Alshurafa
Received: 1 April 2016 / Revised: 27 June 2016 / Accepted: 14 July 2016 / Published: 18 July 2016
(This article belongs to the Special Issue Smart Health)
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Abstract

The assessment of mobility and functional impairments in the elderly is important for early detection and prevention of fall conditions. Falls create serious threats to health by causing disabling fractures that reduce independence in the elderly. Moreover, they exert heavy economic burdens on society due to high treatment costs. Modern smartphones enable the development of innovative mobile health (mHealth) applications by integrating a growing number of inertial and environmental sensors along with the ever-increasing data processing and communication capabilities. Mobility assessment is one of the promising mHealth application domains. In this paper, we introduce a suite of smartphone applications for assessing mobility in the elderly population. The suite currently includes smartphone applications that automate and quantify the following standardized medical tests for assessing mobility: Timed Up and Go (TUG), 30-Second Chair Stand Test (30SCS), and 4-Stage Balance Test (4SBT). For each application, we describe its functionality and a list of parameters extracted by processing signals from smartphone’s inertial sensors. The paper shows the results from studies conducted on geriatric patients for TUG tests and from experiments conducted in the laboratory on healthy subjects for 30SCS and 4SBT tests. View Full-Text
Keywords: mobility assessment; Timed Up and Go test; 30-Second Chair Stand Test; 4-Stage Balance Test; inertial sensors; signal processing; health monitoring mobility assessment; Timed Up and Go test; 30-Second Chair Stand Test; 4-Stage Balance Test; inertial sensors; signal processing; health monitoring
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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. (CC BY 4.0).

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MDPI and ACS Style

Madhushri, P.; Dzhagaryan, A.; Jovanov, E.; Milenkovic, A. An mHealth Tool Suite for Mobility Assessment. Information 2016, 7, 47.

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