2026-06-01T18:57:21Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/378672026-02-03T10:57:03Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Galán-Mercant, Alejandro author Cuesta-Vargas, Antonio author 2014-09-12 Background: The diagnosis of frailty is based on physical impairments and clinicians have indicated that early detection is one of the most effective methods for reducing the severity of physical frailty. Maybe, an alternative to the classical diagnosis could be the instrumentalization of classical functional testing, as Romberg test or Timed Get Up and Go Test. The aim of this study was (I) to measure and describe the magnitude of accelerometry values in the Romberg test in two groups of frail and non-frail elderly people through instrumentation with the iPhone 4®, (II) to analyse the performances and differences between the study groups, and (III) to analyse the performances and differences within study groups to characterise accelerometer responses to increasingly difficult challenges to balance. Methods: This is a cross-sectional study of 18 subjects over 70 years old, 9 frail subjects and 9 non-frail subjects. The non-parametric Mann-Whitney U test was used for between-group comparisons in means values derived from different tasks. The Wilcoxon Signed-Rank test was used to analyse differences between different variants of the test in both independent study groups. Results: The highest difference between groups was found in the accelerometer values with eyes closed and feet parallel: maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.01). Subjects with eyes open and feet parallel, greatest differences found between the groups were in the maximum peak acceleration in the lateral axis (p < 0.01), minimum peak acceleration in the lateral axis (p < 0.01) and minimum peak acceleration from the resultant vector (p < 0.001). Conclusions: The accelerometer fitted in the iPhone 4® is able to study and analyse the kinematics of the Romberg test between frail and non-frail elderly people. Galán-Mercant A, Cuesta-Vargas AI. Mobile Romberg test assessment (mRomberg). BMC Res Notes. 2014 Sep 12;7:640. doi: 10.1186/1756-0500-7-640. PMID: 25217250; PMCID: PMC4167282. https://hdl.handle.net/10630/37867 10.1186/1756-0500-7-640 Informática médica Mobile Romberg test assessment (mRomberg)