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Marker-less versus marker-based driven musculoskeletal models of the spine during static load-handling activities.
Journal of Biomechanics ( IF 2.4 ) Pub Date : 2020-09-09 , DOI: 10.1016/j.jbiomech.2020.110043
F Asadi 1 , N Arjmand 1
Affiliation  

Evaluation of workers’ body posture in workstations is a prerequisite to estimate spinal loads and assess risk of injury for the subsequent design of preventive interventions. The Microsoft Kinect™ sensor is, in this regard, advantageous over the traditional skin-marker-based optical motion capture systems for being marker-less, portable, cost-effective, and easy-to-use in real workplaces. While several studies have demonstrated the validity/reliability of the Kinect for posture measurements especially during gait trials, its capability to adequately drive a detailed spine musculoskeletal model for injury risk assessments remains to be investigated. Lumbosacral (L5-S1) load predictions of a Kinect-driven and a gold-standard marker-based Vicon-driven musculoskeletal model were compared for various standing static load-handling activities at different heights/asymmetry angles/distances. Full body kinematics of eight individuals each performing eighteen activities were simultaneously recorded by a single-front-placed Kinect and a 10-camera Vicon motion capture system and input to AnyBody Modeling System. The predicted spinal loads by the two models were in average different by 17.8 and 25.9% for the L5-S1 disc compressive and shear forces, respectively, with smaller errors for the activities at higher load heights. Some activities performed near the floor could, however, not be recorded by a single-front-placed Kinect sensor due to the joint occlusion. The capability of the Kinect to adequately drive a spine musculoskeletal model depended on the complexity of the activity. While a single front-placed Kinect camera can be used to evaluate spinal loads in a wide range of static/quasi-static activities, cautious should be exercised when evaluating tasks performed near the floor.



中文翻译:

在静态负荷处理活动期间,无标记与基于标记的脊柱驱动肌肉骨骼模型。

评估工人在工作站中的身体姿势是评估脊柱负荷和评估伤害风险的先决条件,以便随后进行预防性干预设计。在这方面,Microsoft Kinect™传感器比传统的基于皮肤标记的光学运动捕获系统更具优势,因为它在实际工作场所无标记,便携式,经济高效且易于使用。尽管几项研究证明了Kinect在姿势测量中的有效性/可靠性(尤其是在步态试验期间),但其充分驱动详细的脊柱肌肉骨骼模型进行伤害风险评估的能力仍有待研究。比较了Kinect驱动和基于金标准标记的Vicon驱动的肌肉骨骼模型的腰ac(L5-S1)负荷预测,以研究在不同高度/不对称角度/距离下的各种静态静负荷处理活动。一个单摆位的Kinect和一个10台摄像机的Vicon运动捕捉系统同时记录了八个人分别执行18个活动的全身运动学,并将其输入到AnyBody建模系统中。两种模型对L5-S1椎间盘的压缩力和剪切力的预测脊柱平均负荷分别平均相差17.8%和25.9%,而在较高负荷高度下的活动误差较小。但是,由于关节闭塞,单面放置的Kinect传感器无法记录在地板附近进行的某些活动。Kinect充分驱动脊柱肌肉骨骼模型的能力取决于活动的复杂性。尽管单个前置Kinect摄像机可用于评估各种静态/准静态活动中的脊柱负荷,但是在评估在地板附近执行的任务时应格外小心。

更新日期:2020-09-18
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