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• W2145233089 abstract "<para xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink> Falls among the elderly population are a major cause of morbidity and injury—particularly among the over 65 years age group. Validated clinical tests and associated models, built upon assessment of functional ability, have been devised to estimate an individual’s risk of falling in the near future. Those identified as at-risk of falling may be targeted for interventative treatment. The migration of these clinical models estimating falls risk to a surrogate technique, for use in the unsupervised environment, might broaden the reach of falls-risk screening beyond the clinical arena. This study details an approach that characterizes the movements of 68 elderly subjects performing a directed routine of unsupervised physical tasks. The movement characterization is achieved through the use of a triaxial accelerometer. A number of fall-related features, extracted from the accelerometry signals, combined with a linear least squares model, maps to a clinically validated measure of falls risk with a correlation of <formula formulatype=inline><tex Notation=TeX>$rho =0.81$</tex></formula><formula formulatype=inline><tex Notation=TeX>$(p < 0.001)$</tex></formula>. </para>" @default.
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• W2145233089 date "2010-03-01" @default.
• W2145233089 modified "2023-09-23" @default.
• W2145233089 title "Longitudinal Falls-Risk Estimation Using Triaxial Accelerometry" @default.
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• W2145233089 doi "https://doi.org/10.1109/tbme.2009.2033038" @default.
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