Project Description

Clin Biomech (Bristol, Avon). 2015 Dec 30;32:8-13. doi: 10.1016/j.clinbiomech.2015.12.009.
A statistical approach to discriminate between non-fallers, rare fallers and frequent fallers in older adults based on posturographic data.
Maranesi E, Merlo A, Fioretti S, Zemp D, Campanini I, Quadri P.

Identification of future non-fallers, infrequent and frequent fallers among older people would permit focusing the delivery of prevention programs on selected individuals. Posturographic parameters have been proven to differentiate between non-fallers and frequent fallers, but not between the first group and infrequent fallers.
In this study, postural stability with eyes open and closed on both a firm and a compliant surface and while performing a cognitive task was assessed in a consecutive sample of 130 cognitively able elderly, mean age 77(7)years, categorized as non-fallers (N=67), infrequent fallers (one/two falls, N=45) and frequent fallers (more than two falls, N=18) according to their last year fall history. Principal Component Analysis was used to select the most significant features from a set of 17posturographic parameters. Next, variables derived from principal component analysis were used to test, in each task, group differences between the three groups.
One parameter based on a combination of a set of Centre of Pressure anterior-posterior variables obtained from the eyes-open on a compliant surface task was statistically different among all groups, thus distinguishing infrequent fallers from both non-fallers (P<0.05) and frequent fallers (P<0.05).
For the first time, a method based on posturographic data to retrospectively discriminate infrequent fallers was obtained. The joint use of both the eyes-open on a compliant surface condition and this new parameter could be used, in a future study, to improve the performance of protocols and to verify the ability of this method to identify new-fallers in elderly without cognitive impairment.
Copyright © 2015 Elsevier Ltd. All rights reserved.
Principal component analysis; center of pressure; elderly; fall risk assessment; posture