Abstract
BackgroundPhysical conditions through gait and other functional task are parameters to consider for frailty detection. The aim of the present study is to measure and describe the variability of acceleration, angular velocity and trunk displacement in the ten meter Extended Timed Get-Up-and-Go test in two groups of frail and non-frail elderly people through instrumentation with the iPhone4® smartphone. Secondly, to analyze the differences and performance of the variance between the study groups (frail and non-frail).This is a cross-sectional study of 30 subjects aged over 65 years, 14 frail subjects and 16 non-frail subjects.ResultsThe highest difference between groups in the Sit-to-Stand and Stand-to-Sit subphases was in the y axis (vertical vector). The minimum acceleration in the Stand-to-Sit phase was -2.69 (-4.17 / -0.96) m/s2 frail elderly versus -8.49 (-12.1 / -5.23) m/s2 non-frail elderly, p < 0.001. In the Gait Go and Gait Come subphases the biggest differences found between the groups were in the vertical axis: -2.45 (-2.77 /-1.89) m/s2 frail elderly versus -5.93 (-6.87 / -4.51) m/s2 non-frail elderly, p < 0.001. Finally, with regards to the turning subphase, the statistically significant differences found between the groups were greater in the data obtained from the gyroscope than from the accelerometer (the gyroscope data for the mean maximum peak value for Yaw movement angular velocity in the frail elderly was specifically 25.60°/s, compared to 112.8°/s for the non-frail elderly, p < 0.05).ConclusionsThe inertial sensor fitted in the iPhone4® is capable of studying and analyzing the kinematics of the different subphases of the Extended Timed Up and Go test in frail and non-frail elderly people. For the Extended Timed Up and Go test, this device allows more sensitive differentiation between population groups than the traditionally used variable, namely time.
Highlights
Physical conditions through gait and other functional task are parameters to consider for frailty detection
With regards to the turning subphase, the statistically significant differences found between the groups were greater in the data obtained from the gyroscope than from the accelerometer
The present study has described and examined the identification, analysis and differentiation in the performance of kinematic variables using the inertial sensor fitted in the iPhone4® during the subphases of the Extended Timed Get-Up-and-Go (ETGUG) test in non-frail and frail elderly persons
Summary
Physical conditions through gait and other functional task are parameters to consider for frailty detection. The changes associated to ageing and frailty bring changes in gait characteristics and the basic functional capacities of the individual [2] This variability in different movement patterns has been interpreted as a more conservative gait pattern in order to increase stability and reduce the risk of. The clinical potential of the TGUG test comes from the sequencing of several basic functional abilities such as standing up and sitting down transitions, transitions which require balance, such as turning, and walking in a straight line [9]. These five sub-phases are common day-to-day activities and are often associated with falls [10]. The TGUG test is currently carried out in an instrumented manner by attaching inertial sensors to the body [2,7,12,13,14,15,16]
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