Robert-Lachaine Xavier, Mecheri Hakim, Larue Christian, Plamondon André
Institut de Recherche Robert Sauvé en Santé et Sécurité du Travail (IRSST), Montréal, QC, Canada.
Med Biol Eng Comput. 2017 Apr;55(4):609-619. doi: 10.1007/s11517-016-1537-2. Epub 2016 Jul 5.
The potential of inertial measurement units (IMUs) for ergonomics applications appears promising. However, previous IMUs validation studies have been incomplete regarding aspects of joints analysed, complexity of movements and duration of trials. The objective was to determine the technological error and biomechanical model differences between IMUs and an optoelectronic system and evaluate the effect of task complexity and duration. Whole-body kinematics from 12 participants was recorded simultaneously with a full-body Xsens system where an Optotrak cluster was fixed on every IMU. Short functional movements and long manual material handling tasks were performed and joint angles were compared between the two systems. The differences attributed to the biomechanical model showed significantly greater (P ≤ .001) RMSE than the technological error. RMSE was systematically higher (P ≤ .001) for the long complex task with a mean on all joints of 2.8° compared to 1.2° during short functional movements. Definition of local coordinate systems based on anatomical landmarks or single posture was the most influent difference between the two systems. Additionally, IMUs accuracy was affected by the complexity and duration of the tasks. Nevertheless, technological error remained under 5° RMSE during handling tasks, which shows potential to track workers during their daily labour.
惯性测量单元(IMU)在人体工程学应用中的潜力似乎很有前景。然而,以往关于IMU的验证研究在分析的关节方面、运动的复杂性和试验持续时间方面并不完整。目的是确定IMU与光电系统之间的技术误差和生物力学模型差异,并评估任务复杂性和持续时间的影响。12名参与者的全身运动学数据通过全身Xsens系统同时记录,其中每个IMU上都固定了一个Optotrak集群。参与者进行了简短的功能性动作和长时间的手动物料搬运任务,并比较了两个系统之间的关节角度。归因于生物力学模型的差异显示,其均方根误差(RMSE)显著大于技术误差(P≤0.001)。与简短的功能性动作期间所有关节平均1.2°相比,长时间复杂任务的RMSE系统性更高(P≤0.001),平均为2.8°。基于解剖标志或单一姿势定义局部坐标系是两个系统之间最具影响力的差异。此外,IMU的准确性受任务复杂性和持续时间的影响。尽管如此,在搬运任务期间,技术误差的RMSE仍保持在5°以下,这表明在日常劳动中跟踪工人具有潜力。