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Smartphone Technology Can Measure Postural Stability and Discriminate Fall Risk in Older Adults

Overview
Journal Gait Posture
Specialty Orthopedics
Date 2018 Oct 20
PMID 30340129
Citations 35
Authors
Affiliations
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Abstract

Background: Falls are the leading cause of injury related death in older adults. Impaired postural stability is a predictor of falls but is seldom objectively assessed in clinical or home settings. Embedded accelerometers within smartphones offer potential to objectively measure postural stability. The purpose of this study was to determine if a smartphone embedded accelerometer can measure static postural stability and distinguish older adults at high levels of fall risk.

Methods: Thirty older adults (age: 65.9 ± 8.8) underwent seven balance tests while standing on a force plate and holding a smartphone against their chest in a standardized order. Participants also completed the Physiological Profile Assessment to assess their fall risk. Center of pressure (COP) parameters from the force plate including velocity in the anterioposterior (AP) and mediolateral (ML) directions and 95% confidence ellipse were derived. Maximum acceleration and root mean square (RMS) in ML, AP and vertical axes were derived from the smartphone. Spearman rank-order correlations between force plate and smartphone measures were conducted, and receiver operating characteristic (ROC) and the area under the curves (AUC) were constructed to distinguish between low and high fall risk.

Results: There were moderate to strong significant correlations between measures derived from the force plate and measures derived from the smartphone during challenging balance conditions (ρ = 0.42-0.81; p < 0.01-0.05). The AUC for ROC plots were significant for all COP measures during challenging balance conditions (p < 0.01-0.05). The AUC for ROC plots were significant for RMS vertical and AP during challenging balance conditions (p = 0.01-0.04).

Significance: This study provides evidence that a smartphone is a valid measure of postural stability and capable of distinguishing fall risk stratification in older adults. There is potential for smartphones to offer objective, fall risk assessments for older adults.

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Anthony E, Kam O, Klisch S, Hazelwood S, Berg-Johansen B Sensors (Basel). 2024; 24(17).

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