Manual and Cognitive Dual Tasks Contribute to Fall-Risk Differentiation in Posturography Measures

in Journal of Applied Biomechanics
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Falls occur in 33% of older adults each year, some leading to moderate to severe injuries. To reduce falls and fall-related injuries, it is important to identify individuals with subtle risk factors elevating their likelihood of falling. The objective of this study was to determine how postural sway measures differed between fallers and nonfallers under standard and dual-task conditions. Quietstanding posturography measures were collected from 150 older adults during standard, cognitive, manual, and cognitive+manual tasks, and analyzed through traditional and nonlinear analyses. Of the traditional measures, M/L sway range and 95% confidence ellipse sway area showed statistically significant differences in all 4 test conditions between fallers and nonfallers. Although the manual dual task showed the most stable balance, effect sizes demonstrated larger differences between fallers and nonfallers. Nonlinear analysis revealed M/L sample entropy and M/L α-scaling exponent differentiating between fallers and nonfallers, with the cognitive task demonstrating larger differences. Based on the results, it is recommended to: (1) apply M/L sway range and 95% confidence ellipse area, (2) use the manual task to differentiate between fallers and nonfallers when using traditional analyses, and (3) use the cognitive task and M/L alpha and M/L sample entropy when using nonlinear analyses.

Beach Sample, Kinney, Smoot Reinert, and Edginton Bigelow are with the Department of Mechanical and Aerospace Engineering, University of Dayton, Dayton, Ohio, USA. Jackson is with the Department of Physical Therapy, University of Dayton, Dayton, Ohio, USA. Diestelkamp is with the Department of Mathematics, University of Dayton, Dayton, Ohio, USA.

Address author correspondence to Renee Beach Sample at renee.b.sample@gmail.com.