McMurtry Shea, Fiedler Goeran
Department of Rehabilitation Science and Technology, University of Pittsburgh, PA, USA.
J Rehabil Assist Technol Eng. 2019 May 13;6:2055668319835701. doi: 10.1177/2055668319835701. eCollection 2019 Jan-Dec.
Artificial turf, soon after being introduced in the 1980s, became associated with an increased injury incidence in football players. While more recent generations of artificial turf have mitigated the problem, perception of the material is still widely negative. So, the decision to play the 2015 Fe'de'ration Internationale de Football Association Women s World Cup in Canada on artificial turf was met with vocal criticism by many players. One common approach is to assess injury incidence to quantify risk differences in playing surfaces. This, however, does not account for possible confounding variables or chronic injuries. Direct measurement of ground reaction forces is difficult because conventional multicamera-based motion capture and force plate equipment are limited in its use outside of dedicated laboratories.
We describe a method of generating realistic force data by using miniature load cells that are installed directly into the weight-bearing structure of the body.
Pilot data show a significant (p<0.01) difference in peak forces on artificial turf (272% of body weight) and natural grass (229% of body weight).
Invasive surgical procedures were avoided by installing the load cell into the prosthesis of an athlete with lower limb loss. As modern prosthetic devices allow a close approximation of able-bodied kinematics and kinetics, such prosthesis-based data are transferable to a general population.
人工草皮在20世纪80年代引入后不久，就与足球运动员受伤发生率增加相关联。虽然最近几代人工草皮已缓解了该问题，但人们对这种材料的看法仍然普遍负面。因此，2015年国际足联女子世界杯在加拿大人工草皮场地举行的决定遭到了许多球员的强烈批评。一种常见方法是评估受伤发生率以量化比赛场地的风险差异。然而，这并未考虑可能的混杂变量或慢性损伤。直接测量地面反作用力很困难，因为传统的基于多摄像机的动作捕捉和测力板设备在专用实验室之外的使用受到限制。
我们描述了一种通过使用直接安装在身体承重结构中的微型称重传感器来生成逼真力数据的方法。
初步数据显示，人工草皮上的峰值力（体重的272%）与天然草坪上的峰值力（体重的229%）存在显著差异（p<0.01）。
通过将称重传感器安装到一名下肢缺失运动员的假肢中，避免了侵入性外科手术。由于现代假肢装置能够非常接近健全人的运动学和动力学，这种基于假肢的数据可推广到普通人群。
