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姿势控制的频率特异性分形分析说明了控制策略。

Frequency-Specific Fractal Analysis of Postural Control Accounts for Control Strategies.

作者信息

Gilfriche Pierre, Deschodt-Arsac Véronique, Blons Estelle, Arsac Laurent M

机构信息

CATIE - Centre Aquitain des Technologies de l'Information et Electroniques, Talence, France.

Univ. Bordeaux, CNRS, Laboratoire IMS, UMR 5218, Talence, France.

出版信息

Front Physiol. 2018 Mar 28;9:293. doi: 10.3389/fphys.2018.00293. eCollection 2018.

Abstract

Diverse indicators of postural control in Humans have been explored for decades, mostly based on the trajectory of the center-of-pressure. Classical approaches focus on variability, based on the notion that if a posture is too variable, the subject is not stable. Going deeper, an improved understanding of underlying physiology has been gained from studying variability in different frequency ranges, pointing to specific short-loops (proprioception), and long-loops (visuo-vestibular) in neural control. More recently, fractal analyses have proliferated and become useful additional metrics of postural control. They allowed identifying two scaling phenomena, respectively in short and long timescales. Here, we show that one of the most widely used methods for fractal analysis, Detrended Fluctuation Analysis, could be enhanced to account for scalings on specific frequency ranges. By computing and filtering a bank of synthetic fractal signals, we established how scaling analysis can be focused on specific frequency components. We called the obtained method Frequency-specific Fractal Analysis (FsFA) and used it to associate the two scaling phenomena of postural control to proprioceptive-based control loop and visuo-vestibular based control loop. After that, convincing arguments of method validity came from an application on the study of unaltered vs. altered postural control in athletes. Overall, the analysis suggests that at least two timescales contribute to postural control: a velocity-based control in short timescales relying on proprioceptive sensors, and a position-based control in longer timescales with visuo-vestibular sensors, which is a brand-new vision of postural control. Frequency-specific scaling exponents are promising markers of control strategies in Humans.

摘要

几十年来,人们一直在探索人类姿势控制的各种指标,主要基于压力中心的轨迹。经典方法侧重于变异性,基于这样的观念,即如果姿势变异性太大,受试者就不稳定。深入研究后,通过研究不同频率范围内的变异性,对潜在生理学有了更好的理解,这指向了神经控制中的特定短环(本体感觉)和长环(视觉 - 前庭)。最近,分形分析大量涌现,并成为姿势控制的有用附加指标。它们允许识别分别在短和长时间尺度上的两种标度现象。在这里,我们表明,分形分析中最广泛使用的方法之一,去趋势波动分析,可以得到改进,以考虑特定频率范围内的标度。通过计算和滤波一组合成分形信号,我们确定了如何将标度分析聚焦于特定频率成分。我们将获得的方法称为频率特定分形分析(FsFA),并使用它将姿势控制的两种标度现象与基于本体感觉的控制环和基于视觉 - 前庭的控制环联系起来。此后,通过在运动员姿势控制未改变与改变的研究中的应用,有力地证明了该方法的有效性。总体而言,分析表明至少有两个时间尺度对姿势控制有贡献:短时间尺度上基于速度的控制依赖于本体感觉传感器,长时间尺度上基于位置的控制使用视觉 - 前庭传感器,这是对姿势控制的全新视角。频率特定标度指数有望成为人类控制策略的标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c79c/5883185/0d88871ae8af/fphys-09-00293-g0001.jpg

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