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压力中心(COP)变量评估老年人站立平衡:算法和开放获取代码。

A review of center of pressure (COP) variables to quantify standing balance in elderly people: Algorithms and open-access code.

机构信息

Centre Borelli UMR 9010/Université Paris-Saclay, ENS Paris-Saclay, CNRS, SSA, Inserm, Université de Paris, Paris, France.

ORPEA Group, Puteaux, France.

出版信息

Physiol Rep. 2021 Nov;9(22):e15067. doi: 10.14814/phy2.15067.

Abstract

Postural control is often quantified by recording the trajectory of the center of pressure (COP)-also called stabilogram-during human quiet standing. This quantification has many important applications, such as the early detection of balance degradation to prevent falls, a crucial task whose relevance increases with the aging of the population. Due to the complexity of the quantification process, the analyses of sway patterns have been performed empirically using a number of variables, such as ellipse confidence area or mean velocity. This study reviews and compares a wide range of state-of-the-art variables that are used to assess the risk of fall in elderly from a stabilogram. When appropriate, we discuss the hypothesis and mathematical assumptions that underlie these variables, and we propose a reproducible method to compute each of them. Additionally, we provide a statistical description of their behavior on two datasets recorded in two elderly populations and with different protocols, to hint at typical values of these variables. First, the balance of 133 elderly individuals, including 32 fallers, was measured on a relatively inexpensive, portable force platform (Wii Balance Board, Nintendo) with a 25-s open-eyes protocol. Second, the recordings of 76 elderly individuals, from an open access database commonly used to test static balance analyses, were used to compute the values of the variables on 60-s eyes-open recordings with a research laboratory standard force platform.

摘要

姿势控制通常通过记录人体在安静站立时的重心(COP)轨迹(也称为稳定图)来进行量化。这种量化方法有许多重要的应用,例如早期检测平衡能力下降以防止跌倒,这是一个非常重要的任务,随着人口老龄化的加剧,其相关性越来越高。由于量化过程的复杂性,使用了许多变量(如椭圆置信区域或平均速度)对摇摆模式进行了经验分析。本研究回顾并比较了广泛用于评估老年人跌倒风险的最新变量,从稳定图来看。在适当的情况下,我们讨论了这些变量所依据的假设和数学假设,并提出了一种可重现的方法来计算每个变量。此外,我们还提供了在两个具有不同协议的老年人群体中记录的两个数据集上这些变量的行为的统计描述,以暗示这些变量的典型值。首先,使用相对便宜、便携式的力平台(任天堂 Wii 平衡板)对 133 名老年人(包括 32 名跌倒者)的平衡能力进行了测量,测量时间为 25 秒睁眼协议。其次,使用来自一个开放获取数据库的 76 名老年人的记录,在研究实验室标准力平台上对 60 秒睁眼记录计算变量值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8110/8623280/06b78d5d1dd3/PHY2-9-e15067-g006.jpg

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