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Estimating fall risk with inertial sensors using gait stability measures that do not require step detection

RIVA F; TOEBES MJ; PIJNAPPELS M; STAGNI R; VAN DIEEN JH
GAIT POSTURE , 2013, vol. 38, n° 2, p. 170-174
Doc n°: 166818
Localisation : Documentation IRR

D.O.I. : http://dx.doi.org/DOI:10.1016/j.gaitpost.2013.05.002
Descripteurs : DF11 - POSTURE. STATION DEBOUT

Falls have major consequences both at societal (health-care and economy) and
individual (physical and psychological) levels. Questionnaires to assess fall
risk are commonly used in the clinic, but their predictive value is limited.
Objective methods, suitable for clinical application, are hence needed to obtain
a quantitative assessment of individual fall risk. Falls in older adults often
occur during walking and trunk position is known to play a critical role in
balance control. Therefore, analysis of trunk kinematics during gait could
present a viable approach to the development of such methods. In this study,
nonlinear measures such as harmonic ratio (HR), index of harmonicity (IH),
multiscale entropy (MSE) and recurrence quantification analysis (RQA) of trunk
accelerations were calculated. These measures are not dependent on step
detection, a potentially critical source of error. The aim of the present study
was to investigate the association between the aforementioned measures and fall
history in a large sample of subjects (42 fallers and 89 non - fallers) aged 50
or older. Univariate associations with fall history were found for MSE and RQA
parameters in the AP direction; the best classification results were obtained for
MSE with scale factor tau = 2 and for maximum length of diagonals in RQA (72.5%
and 71% correct classifications, respectively). MSE and RQA were found to be
positively associated with fall history and could hence represent useful tools in
the identification of subjects for fall prevention programs.
CI - Copyright (c) 2013 Elsevier B.V. All rights reserved.

Langue : ANGLAIS

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