利用可穿戴式加速度计建立跑步过程中垂直地面反作用力预测模型:敏感性研究

IF 1.9 Q3 ENGINEERING, MECHANICAL
Vibration Pub Date : 2023-09-12 DOI:10.3390/vibration6030042
Thomas Provot, Samaneh Choupani, Maxime Bourgain, Laura Valdes-Tamayo, Delphine Chadefaux
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引用次数: 0

摘要

在跑步过程中地面垂直反作用力的估算是理解跑步机理的必要条件。为此目的,使用武力平台是根本的。然而,为了将vgrf的研究扩展到真实条件,可穿戴加速度计是一种很有前途的替代力平台,其使用通常仅限于实验室环境。本研究的目的是利用可穿戴式加速度计和逐步回归算法建立VGRF模型。利用参与者在100个姿态中收集的vgrf和加速度信号,开发并验证了几个模型。对8名参与者进行了验证模型的测试。在一项敏感性研究中,在截止频率≤25 Hz和30至90个姿态的模型中观察到最强的相关性。经过验证阶段,10个最佳模型在离散VGRF参数估计上的平均相对差异较小(≤10%),即被动峰(εpp=6.26%)、主动峰(εap=2.22%)和加载率(εlr=2.17%)。结果表明,开发个性化模型更适合于实现最佳估计。所提出的方法为使用有限数量的可穿戴传感器在实际条件下监测vgrf打开了许多视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Wearable Accelerometers to Develop a Vertical Ground Reaction Force Prediction Model during Running: A Sensitivity Study
The estimation of vertical ground reaction forces (VGRFs) during running is necessary to understand running mechanisms. For this purpose, the use of force platforms is fundamental. However, to extend the study of VGRFs to real conditions, wearable accelerometers are a promising alternative to force platforms, whose use is often limited to the laboratory environment. The objective of this study was to develop a VGRF model using wearable accelerometers and a stepwise regression algorithm. Several models were developed and validated using the VGRFs and acceleration signals collected during 100 stances performed by one participant. The validated models were tested on eight participants. In a sensitivity study, the strongest correlations were observed at cut-off frequencies of ≤25 Hz and in models developed with 30 to 90 stances. After the validation phase, the 10 best models had, on average, low relative differences (≤10%) in the estimation of discrete VGRF parameters, i.e., the passive peak (εpp=6.26%), active peak (εap=2.22%), and loading rate (εlr=2.17%). The results indicate that the development of personalized models is more suitable for achieving the best estimates. The proposed methodology opens many perspectives for monitoring VGRFs under real conditions using a limited number of wearable sensors.
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来源期刊
CiteScore
3.20
自引率
0.00%
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