Galán-Mercant Alejandro, Cuesta-Vargas Antonio I
Physiotherapy Department, Faculty of Health Sciences, IBIMA, Universidad de Malaga, Av/Arquitecto Peñalosa s/n (Teatinos Campus Expansion), 29009 Málaga, Spain.
BMC Res Notes. 2014 Feb 21;7:100. doi: 10.1186/1756-0500-7-100.
Physical 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.
The 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).
The 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.
通过步态和其他功能任务所反映的身体状况是用于检测衰弱的参数。本研究的目的是通过使用iPhone4®智能手机进行仪器测量，来测量和描述两组衰弱和非衰弱老年人在十米延长计时起立行走测试中的加速度、角速度和躯干位移的变异性。其次，分析研究组（衰弱和非衰弱）之间方差的差异和表现。这是一项针对30名65岁以上受试者的横断面研究，其中14名衰弱受试者和16名非衰弱受试者。
在坐立和站立坐两个子阶段中，组间差异最大的是y轴（垂直向量）。在站立坐阶段，衰弱老年人的最小加速度为-2.69（-4.17/-0.96）m/s²，而非衰弱老年人为-8.49（-12.1/-5.23）m/s²，p＜0.001。在步态去和步态回子阶段，组间最大差异出现在垂直轴上：衰弱老年人为-2.45（-2.77/-1.89）m/s²，而非衰弱老年人为-5.93（-6.87/-4.51）m/s²，p＜0.001。最后，关于转身子阶段，组间在陀螺仪数据中发现的统计学显著差异大于加速度计数据（衰弱老年人偏航运动角速度的平均最大峰值的陀螺仪数据具体为25.60°/s，而非衰弱老年人为112.8°/s，p＜0.05）。
安装在iPhone4®中的惯性传感器能够研究和分析衰弱和非衰弱老年人在延长计时起立行走测试不同子阶段的运动学。对于延长计时起立行走测试，该设备比传统使用的变量（即时间）能更敏感地区分不同人群组。
