评估行走的稳定反馈控制:教程。

IF 2 4区 医学 Q3 NEUROSCIENCES
Jaap H. van Dieën , Sjoerd M. Bruijn , Maarten Afschrift
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引用次数: 0

摘要

要想在行走时不摔倒,就必须稳定身体质心相对于支撑基座的轨迹。模型研究表明,这需要主动的反馈控制,即神经系统必须处理有关身体状态的感官信息,以便向肌肉发出下行运动指令,从而稳定行走,尤其是在内侧方向。双足步态的稳定具有挑战性,老年人和患病者的双足步态稳定可能会受损。在本教程中,我们将说明如何利用步态分析来评估步态的稳定反馈控制。我们介绍的方法既有需要有限输入数据的方法(例如仅在脚部和骨盆上放置标记的位置数据),也有需要全身运动学和肌电图的方法。分析范围从简单的运动学分析到逆动力学分析。这些方法从三个层面对人类行走的稳定反馈控制进行评估:1)质心运动水平和水平地面反作用力;2)质心运动水平和脚的位置;3)质心运动水平和关节力矩或肌肉活动。我们展示了如何计算这些信息,并提供了一个 GitHub 存储库 (https://github.com/VU-HMS/Tutorial-stabilizing-walking),其中包含用于计算这些信息的开放式 Matlab 和 Python 代码。最后,我们将讨论从这些信息中可以了解到哪些反馈控制信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Assessment of stabilizing feedback control of walking: A tutorial

Walking without falling requires stabilization of the trajectory of the body center of mass relative to the base of support. Model studies suggest that this requires active, feedback control, i.e., the nervous system must process sensory information on the state of the body to generate descending motor commands to the muscles to stabilize walking, especially in the mediolateral direction. Stabilization of bipedal gait is challenging and can be impaired in older and diseased individuals. In this tutorial, we illustrate how gait analysis can be used to assess the stabilizing feedback control of gait. We present methods ranging from those that require limited input data (e.g. position data of markers placed on the feet and pelvis only) to those that require full-body kinematics and electromyography. Analyses range from simple kinematics analyses to inverse dynamics. These methods assess stabilizing feedback control of human walking at three levels: 1) the level of center of mass movement and horizontal ground reaction forces, 2) the level of center of mass movement and foot placement and 3) the level of center of mass movement and the joint moments or muscle activity. We show how these can be calculated and provide a GitHub repository (https://github.com/VU-HMS/Tutorial-stabilizing-walking) which contains open access Matlab and Python code to calculate these. Finally, we discuss what information on feedback control can be learned from each of these.

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来源期刊
CiteScore
4.70
自引率
8.00%
发文量
70
审稿时长
74 days
期刊介绍: Journal of Electromyography & Kinesiology is the primary source for outstanding original articles on the study of human movement from muscle contraction via its motor units and sensory system to integrated motion through mechanical and electrical detection techniques. As the official publication of the International Society of Electrophysiology and Kinesiology, the journal is dedicated to publishing the best work in all areas of electromyography and kinesiology, including: control of movement, muscle fatigue, muscle and nerve properties, joint biomechanics and electrical stimulation. Applications in rehabilitation, sports & exercise, motion analysis, ergonomics, alternative & complimentary medicine, measures of human performance and technical articles on electromyographic signal processing are welcome.
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