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通过动态建模开发低成本力跑步机。

Developing a Low-Cost Force Treadmill via Dynamic Modeling.

机构信息

Department of Mechanical and Electromechanical Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan.

Department of Sports Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.

出版信息

J Healthc Eng. 2017;2017:9875471. doi: 10.1155/2017/9875471. Epub 2017 Jun 4.

DOI:10.1155/2017/9875471
PMID:29065677
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5474287/
Abstract

By incorporating force transducers into treadmills, force platform-instrumented treadmills (commonly called force treadmills) can collect large amounts of gait data and enable the ground reaction force (GRF) to be calculated. However, the high cost of force treadmills has limited their adoption. This paper proposes a low-cost force treadmill system with force sensors installed underneath a standard exercise treadmill. It identifies and compensates for the force transmission dynamics from the actual GRF applied on the treadmill track surface to the force transmitted to the force sensors underneath the treadmill body. This study also proposes a testing procedure to assess the GRF measurement accuracy of force treadmills. Using this procedure in estimating the GRF of "walk-on-the-spot motion," it was found that the total harmonic distortion of the tested force treadmill system was about 1.69%, demonstrating the effectiveness of the approach.

摘要

通过在跑步机中加入力传感器,力平台式跑步机(通常称为力跑步机)可以收集大量步态数据并计算地面反力(GRF)。然而,力跑步机的高成本限制了它们的采用。本文提出了一种低成本的力跑步机系统,在标准跑步机下方安装力传感器。它可以识别和补偿从实际施加在跑步机轨道表面的 GRF 到传递到跑步机机身下方力传感器的力的力传递动力学。本研究还提出了一种测试程序来评估力跑步机的 GRF 测量精度。使用该程序估计“原地踏步运动”的 GRF 时,发现测试的力跑步机系统的总谐波失真约为 1.69%,表明该方法的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/8c29769f4111/JHE2017-9875471.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/1e107b2fbf8d/JHE2017-9875471.001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/8c29769f4111/JHE2017-9875471.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/1e107b2fbf8d/JHE2017-9875471.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/4e252674b70b/JHE2017-9875471.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/ddb81114cd18/JHE2017-9875471.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/f18eb05fe27a/JHE2017-9875471.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/da2ff9cd08ef/JHE2017-9875471.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/bcf935b14ce7/JHE2017-9875471.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e77e/5474287/8c29769f4111/JHE2017-9875471.007.jpg

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