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A novel kinematic detection of foot-strike and toe-off events during noninstrumented treadmill running to estimate contact time
Journal of Biomechanics ( IF 2.4 ) Pub Date : 2021-09-06 , DOI: 10.1016/j.jbiomech.2021.110737
Aurélien Patoz 1 , Thibault Lussiana 2 , Cyrille Gindre 3 , Davide Malatesta 4
Affiliation  

Contact time (tc) relies upon the accuracy of foot-strike and toe-off events, for which ground reaction force (GRF) is the gold standard. However, force plates are not always available, e.g., when running on a noninstrumented treadmill. In this situation, a kinematic algorithm (KA) – an algorithm based on motion capture data – might be used if it performs equally for all foot-strike angles across speeds. The purpose of this study was to propose a novel KA, using a combination of heel and toe kinematics (three markers per foot), to detect foot-strike and toe-off and compare it to GRF at different speeds and across foot-strike angles. One hundred runners ran at 9 km/h, 11 km/h, and 13 km/h. Force data and whole-body kinematic data were acquired by an instrumented treadmill and optoelectronic system. Foot-strike and toe-off showed small systematic biases between GRF and KA at all speeds (≤5 ms), except toe-off at 11 km/h (no bias). The root mean square error (RMSE) was ≤9 ms and was mostly constant across foot-strike angles for toe-off (7.4 ms) but not for foot-strike (4.1–11.1 ms). Small systematic biases (≤8 ms) and significant differences (P ≤ 0.01) were reported for tc at all speeds, and the RMSE was ≤14 ms (≤5%). The RMSE for tc increased with increasing foot-strike angle (3.5–5.4%). Nonetheless, this novel KA computed smaller errors than existing methods for foot-strike, toe-off, and tc. Therefore, this study supports the use of this novel KA to accurately estimate foot-strike, toe-off, and tc from kinematic data obtained during noninstrumented treadmill running independent of the foot-strike angle.



中文翻译:

一种新的运动学检测在非仪表跑步机运行过程中足部撞击和脚趾离地事件以估计接触时间

联系时间(C) 依赖于足部撞击和脚趾离地事件的准确性,地面反作用力 (GRF) 是黄金标准。然而,测力台并不总是可用的,例如,在非器械跑步机上跑步时。在这种情况下,如果运动学算法 (KA) 是一种基于运动捕捉数据的算法,则可以使用它,前提是它对跨速度的所有足部撞击角度的表现都相同。本研究的目的是提出一种新颖的 KA,结合使用足跟和足尖运动学(每只脚三个标记)来检测足部着地和足尖离地,并将其与不同速度和跨足部着地角度的 GRF 进行比较. 一百名跑步者以 9 公里/小时、11 公里/小时和 13 公里/小时的速度跑步。力数据和全身运动学数据由仪表化跑步机和光电系统采集。除了 11 公里/小时的脚尖离地(无偏差)外,在所有速度下(≤ 5 毫秒),脚触地和脚尖离地在 GRF 和 KA 之间显示出小的系统偏差。均方根误差 (RMSE) ≤ 9 ms,并且在脚尖离地 (7.4 ms) 的足部撞击角度上大部分是恒定的,但足部撞击 (4.1-11.1 ms) 则不然。小的系统偏差(≤8 ms)和显着差异(P  ≤ 0.01) 被报告为C在所有速度下,RMSE ≤ 14 ms (≤ 5%)。RMSE 为C随着足部撞击角度的增加而增加(3.5-5.4%)。尽管如此,这种新颖的 KA 计算的误差比现有的足部撞击、脚趾离地和C. 因此,本研究支持使用这种新颖的 KA 来准确估计足部着地、脚趾离地和C 从非仪表跑步机运行期间获得的运动学数据与足部撞击角度无关。

更新日期:2021-09-10
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