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• W3165320239 endingPage "102807" @default.
• W3165320239 startingPage "102807" @default.
• W3165320239 abstract "Studying the dynamics of nonlinear systems can provide additional information about the variability structure of the system. Within the current study, we examined the application of regularity and local stability measures to capture motor function alterations due to dual-tasking using a previously validated upper-extremity function (UEF). We targeted young (ages 18 and 30 years) and older adults (65 years or older) with normal cognition based on clinical screening. UEF involved repetitive elbow flexion without counting (ST) and while counting backward by one (DT1) or three (DT3). We measured the regularity (measured by sample entropy (SE)), local stability (measured by the largest Lyapunov exponent (LyE)), as well as conventional peak-dependent variability measures (coefficient of variation of kinematics parameters) to capture motor dynamic alterations due to dual-tasking. Within both groups, only SE showed significant differences between all pairs of UEF condition comparisons, even ST vs DT1 (p = 0.007, effect size = 0.507), for which no peak-dependent parameter showed significant difference. Among all measures, the only parameter that showed a significant difference between young and older adults was LyE (p < 0.001, effect size = 0.453). Current findings highlight the potential of nonlinear analysis to detect aging-related alterations among cognitively healthy participants." @default.
• W3165320239 created "2021-06-07" @default.
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• W3165320239 date "2021-08-01" @default.
• W3165320239 modified "2023-09-30" @default.
• W3165320239 title "Nonlinear analysis of the movement variability structure can detect aging-related differences among cognitively healthy individuals" @default.
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• W3165320239 doi "https://doi.org/10.1016/j.humov.2021.102807" @default.
• W3165320239 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8319078" @default.
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• W3165320239 hasPublicationYear "2021" @default.
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