DEIS - Department of Electronics, Computer Sciences and Systems, University of Bologna, Italy.
Gait Posture. 2013 Jun;38(2):170-4. doi: 10.1016/j.gaitpost.2013.05.002. Epub 2013 May 28.
Falls have major consequences both at societal (health-care and economy) and individual (physical and psychological) levels. Questionnaires to assess fall risk are commonly used in the clinic, but their predictive value is limited. Objective methods, suitable for clinical application, are hence needed to obtain a quantitative assessment of individual fall risk. Falls in older adults often occur during walking and trunk position is known to play a critical role in balance control. Therefore, analysis of trunk kinematics during gait could present a viable approach to the development of such methods. In this study, nonlinear measures such as harmonic ratio (HR), index of harmonicity (IH), multiscale entropy (MSE) and recurrence quantification analysis (RQA) of trunk accelerations were calculated. These measures are not dependent on step detection, a potentially critical source of error. The aim of the present study was to investigate the association between the aforementioned measures and fall history in a large sample of subjects (42 fallers and 89 non - fallers) aged 50 or older. Univariate associations with fall history were found for MSE and RQA parameters in the AP direction; the best classification results were obtained for MSE with scale factor τ = 2 and for maximum length of diagonals in RQA (72.5% and 71% correct classifications, respectively). MSE and RQA were found to be positively associated with fall history and could hence represent useful tools in the identification of subjects for fall prevention programs.
跌倒在社会（医疗保健和经济）和个人（身体和心理）层面都有重大后果。评估跌倒风险的问卷在临床上常用，但预测价值有限。因此，需要适合临床应用的客观方法来对个体跌倒风险进行定量评估。老年人跌倒通常发生在行走过程中，而躯干姿势已知在平衡控制中起着关键作用。因此，对步态过程中的躯干运动学进行分析可能是开发此类方法的可行方法。在本研究中，计算了躯干加速度的非线性测量值，如谐波比（HR）、调和指数（IH）、多尺度熵（MSE）和递归定量分析（RQA）。这些测量值不依赖于步检测，步检测是潜在的关键误差源。本研究的目的是在一个由 50 岁及以上的受试者（42 名跌倒者和 89 名非跌倒者）组成的大样本中，研究上述测量值与跌倒史之间的关联。在 AP 方向上，与跌倒史有单变量关联的是 MSE 和 RQA 参数；对于 MSE，最佳分类结果是尺度因子τ=2，对于 RQA 的最大对角线长度（分别为 72.5%和 71%的正确分类）。MSE 和 RQA 与跌倒史呈正相关，因此可以作为识别跌倒预防计划对象的有用工具。
