Abstract
Frailty is a common condition in older adults, characterized, among other things, by impairments in gait and movement patterns. The proposed FRAILPOL repository addresses the critical gap in geriatric research by offering a comprehensive, open-access, five body-worn inertial sensors (ankles, wrists, and back of sacrum) signals recorded during the Time Up and Go test of 668 participants, community-dwelling older adults. The gait data, as well as the stride-based spatio-temporal parameters along with demographic and health-related information, including cognitive health data, have been grouped according to established clinical criteria into three classes (robust, pre-frailty, and frailty). The technical verification includes classification by reporting results for both binary (robust, frailty) and multi-class (robust, pre-frailty, frailty) classification using classical machine learning models with acceptable accuracy.
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CITATION STYLE
Szczȩsna, A., Amjad, A., Błaszczyszyn, M., Sacha, M., Feusette, P., Zieliński, R., … Sacha, J. (2026). Database for Prevalence and Determinants of Frailty in the Elderly with Quantifying Functional Mobility. Scientific Data , 13(1). https://doi.org/10.1038/s41597-026-06854-8
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