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  4. Gender and age-related decline in lower limb standing muscle strength: benchmarking for rehabilitation assessment

Gender and age-related decline in lower limb standing muscle strength: benchmarking for rehabilitation assessment

Citation Link: https://doi.org/10.15480/882.16435
Publikationstyp
Journal Article
Date Issued
2025-12-22
Sprache
English
Author(s)
Raudonis, Vidas
Staneikaite, Viktorija
Kubiliūtė, Ugnė
Kubilius, Raimondas
Grube, Sarah
Medizintechnische und Intelligente Systeme E-1
Neidhardt, Maximilian
Medizintechnische und Intelligente Systeme E-1
Schlaefer, Alexander
Medizintechnische und Intelligente Systeme E-1
Tankevičius, Gediminas
TORE-DOI
10.15480/882.16435
TORE-URI
https://hdl.handle.net/11420/60711
Journal
Sensors
Volume
26
Issue
1
Article Number
69
Citation
Sensors 26 (1): 69 (2025)
Publisher DOI
10.3390/s26010069
Scopus ID
2-s2.0-105027047299
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
This study aimed to demonstrate a novel sensor-based measuring stand for objective assessment of multi-directional lower limb muscle strength and to establish essential, age- and gender-stratified normative benchmarks. This cross-sectional study measured relative leg strength (N/kg) across six standing movements in 99 healthy, non-professional athletes (males and females aged 20–30, 40–50, and 60–70 years). Results confirmed that men exhibited significantly greater strength than women across all six directions (17% to 35% difference). Furthermore, a marked age-related decline was consistently observed in both sexes, with the largest and most clinically relevant differences (often exceeding 30%) concentrated in the transition to the 60–70-year range. Methodologically, these findings are limited to demonstrating age-related differences rather than longitudinal decline and are specific to an active, healthy cohort. This study demonstrates the sensor-based stand as an efficient, objective tool for comprehensive strength assessment, but its clinical utility is prospective and requires further validation against diverse and pathological patient populations.
DDC Class
610: Medicine, Health
621.3: Electrical Engineering, Electronic Engineering
Funding(s)
Centre of Excellence of Al for Sustainable Living and Working
Lizenz
https://creativecommons.org/licenses/by/4.0/
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