Digital Health | 2019

K-D Balance: An objective measure of balance in tandem and double leg stances

 
 
 
 

Abstract


Background and objective Subjective grade-based scoring balance assessments tend to be lengthy and have demonstrated poor repeatability and reliability. This study examined the reliability of a mobile balance assessment tool and differences in balance measurements between individuals at risk for a balance deficit secondary to a diagnosed neurological or musculoskeletal condition and a control group of healthy individuals. Methods Objective balance testing was measured using K-D Balance on a compatible iPhone. Seventy-seven participants were enrolled (control group, n\u2009=\u200944; group at risk for balance deficits, n\u2009=\u200933). Mean and standard deviation of K-D Balance were recorded for each stance. Intra-rater reliability was calculated by repeating the trial. Results Overall balance scores were superior for the control group compared with the group at risk for balance deficits in double leg stance (mean (SD): 0.15 (0.12) versus 0.18 (0.13), p\u2009=\u20090.260), tandem stance right leg (mean (SD): 0.27 (0.17) versus 0.45 (0.49), p\u2009=\u20090.028), and tandem stance left leg (mean (SD): 0.26 (0.17) versus 0.35 (0.35), p\u2009=\u20090.136). Intra-rater reliability was good to excellent for K-D Balance double leg stance (intra-class correlation coefficient (ICC)\u2009=\u20090.80, 95% confidence interval (CI) 0.58–1.03), tandem stance right leg (ICC\u2009=\u20090.96, 95% CI 0.86–1.06) and tandem stance left leg (ICC\u2009=\u20090.98, 95% CI 0.95–1.0). Conclusions K-D Balance revealed differences in balance performance between healthy individuals compared with individuals with neurological or musculoskeletal impairment. Objective balance measures may improve the accuracy and reliability of clinical balance assessment by detecting subtle differences in balance and aid in early detection of diseases that impair balance.

Volume 5
Pages None
DOI 10.1177/2055207619885573
Language English
Journal Digital Health

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