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ABSTRACT: Background
Fall(s) are a significant cause of morbidity and mortality especially amongst elderly with polyneuropathy and cognitive decline. Conventional fall risk assessment tools are prone to low predictive values and do not address specific vulnerabilities. This study seeks to advance the development of an innovative, engaging fall prediction tool for a high-risk cohort diagnosed with diabetes.Methods
In this proof-of-concept cohort study, between July 01, 2020, and May 31, 2022, 152 participants with diabetes performed clinical examinations to estimate individual risks of fall (timed "up and go" (TUG) test, dynamic gait index (DGI), Berg-Balance-Scale (BBS)) and participated in a video game-based fall risk assessment with sensor-equipped insoles as steering units. The pa
SUBMITTER: Ming A
PROVIDER: S-EPMC11638629 | biostudies-literature | 2024 Dec
REPOSITORIES: biostudies-literature