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步速控制步态分析中绊倒风险的研究。

Study on Tripping Risks in Fast Walking through Cadence-Controlled Gait Analysis.

机构信息

Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Douliu, Yunlin 640, Taiwan.

Department of Physical Medicine and Rehabilitation, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan 600, Taiwan.

出版信息

J Healthc Eng. 2018 May 24;2018:2723178. doi: 10.1155/2018/2723178. eCollection 2018.

DOI:10.1155/2018/2723178
PMID:30002803
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5996466/
Abstract

Fast walking is a common exercise for most people to promote health. However, a higher cadence due to fast walking on ordinary or uneven ground raises the risk of tripping. To investigate the tripping issue, research to observe the gait in fast walking is needed. To explore the relationship between fast gait and the risk of tripping, a gait recording system with a specific synchronization mechanism was developed in this work. The system can acquire gait signals from wearable sensors and action cameras at different cadences. Meanwhile, algorithms for gait cycle segmentation and characteristic extraction were proposed for analyzing a fast gait. In the gait analysis, the correlations of low, moderate, and high cadence in cueing and no cueing gaits were computed, and two results were obtained. First, the higher the cadence is, the larger the motion strength in the terminal foot swing will be and the smaller the motion strength at the starting foot swing. Second, the decreased distance of foot clearance becomes more conspicuous as the cadence increased, especially if one is walking more than 120 beats. The results indicate that fast walking with bigger strides and lower cadence is the best way to maintain safety in moving over ordinary ground.

摘要

快走是大多数人促进健康的常见运动方式。然而,由于在普通或不平坦的地面上快速行走而导致的更高步频会增加绊倒的风险。为了研究绊倒问题,需要进行观察快走步态的研究。为了探究快速步态与绊倒风险之间的关系,本工作开发了一种具有特定同步机制的步态记录系统。该系统可以从可穿戴传感器和动作摄像机以不同的步频获取步态信号。同时,还提出了用于分析快速步态的步态周期分割和特征提取算法。在步态分析中,计算了提示和无提示步态中低、中、高步频的相关性,得到了两个结果。首先,步频越高,终端脚摆动的运动强度越大,起始脚摆动的运动强度越小。其次,随着步频的增加,足清除距离的减小变得更加明显,尤其是在行走超过 120 拍时。结果表明,在普通地面上移动时,大步幅和低步频的快速行走是保持安全的最佳方式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d77e/5996466/e5f4b4c36991/JHE2018-2723178.alg.002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d77e/5996466/02af82f6d731/JHE2018-2723178.001.jpg
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