Aging impairs bimanual isometric force smoothness
DOI:
https://doi.org/10.17179/excli2026-9581Keywords:
older adults, force control, fine motor control, force variability, YANKAbstract
Older adults normally showed impaired fine motor control capabilities, as indicated by increased force error and variability during submaximal force control tasks. However, whether aging additionally disrupts temporal smoothness of the force trajectory remains unclear beyond the magnitude of force fluctuation. This study investigated age-related changes in bimanual isometric force smoothness using YANK analysis (i.e., time-derivative of force; dF/dt). Fifteen younger adults (mean ± SD of age = 25.4 ± 2.5 years) and fifteen older adults (mean ± SD of age = 64.9 ± 6.5 years) performed bimanual hand-grip isometric force control at 10 % of maximum voluntary contraction across the vision and no-vision conditions. Force accuracy (relative root-mean-square error; rRMSE), variability (coefficient of variation; CV), smoothness (YANK), and interlimb force coordination (correlation coefficient) were quantified. Receiver operating characteristic (ROC) curve and Pearson’s correlation analyses were conducted to evaluate the discriminative ability of each variable and potential relationships between YANK and conventional force control variables. Older adults showed significantly higher YANK values than younger adults in both vision and no-vision conditions, indicating reduced force smoothness. Greater rRMSE, CV, and correlation coefficient values for older adults were observed only in the vision condition. The ROC curve analysis revealed that YANK effectively discriminated between the younger and older adults in both vision and no-vision conditions. For older adults, increased YANK was significantly correlated with greater rRMSE and CV in the vision condition and with greater CV in the no-vision condition, whereas no significant correlations appeared in younger adults. These findings suggest the YANK approach can capture age-related fine motor control deficits that conventional variability measures may overlook.
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Copyright (c) 2026 Hajun Lee, Hanall Lee, Jinwon Shin, Eo-Jin Son, Nyeonju Kang

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