上肢肌肉骨骼疾病重复动作风险评估的自动平台-初步结果。

P. Aqueveque, Manuel Gutiérrez, Guisella Peña, Enrique I. Germany, Britam Gómez, Gustavo Retamal, P. Ortega-Bastidas
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引用次数: 0

摘要

与工作相关的肌肉骨骼疾病是工人在处理重复性任务时健康的主要问题。职业重复性动作指数(Occupational repeat Actions Index, OCRA)是一种应用最广泛的方法,用于确定重复性动作对上肢的危害。传统的风险评估包括观察和记录整个工作日或部分工作日。这种观察性评估取决于评估者的专业知识,这导致评估者之间的结果差异,即使是相同的工作。本文介绍了一个平台的初步结果,该平台将运动捕捉数据与数字化OCRA索引方法相结合,用于重复任务条件下的风险分类。在一个受控的实验室环境中,对10名健康受试者进行重复性动作任务,其中使用光学和惯性传感器来捕捉运动。将体段位置、位移和关节角输入平台,比较其处理时间和可靠性。虽然结果表明光学系统比惯性传感器具有更好的姿态评估性能,但由于光学标记在工作设置中遮挡导致测量误差,光学系统具有更好的实际适用性。此外,惯性系统更有可能在实际工作场景中使用,因为它们易于使用和便携。最后,与传统观测方法相比,惯性传感器与数字化OCRA指数方法平台相结合,有效地减少了67%的评估时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Platform for Upper Extremity Musculoskeletal Disorder Risks Estimation from Repetitive Actions -Preliminary results.
Work-related musculoskeletal disorders is a major problem for worker’s health when dealing with repetitive tasks. The Occupational Repetitive Actions Index (OCRA) is one of the most widely used methods for determining upper extremity risk from repetitive actions. Traditional risk assessment consists in observing and recording the entire workday or part of it. This observational assessment depends on the evaluator’s expertise, which lead to inter-evaluator variability in the results even for the same job. This paper presents preliminary results of a platform that combines motion capture data with a digitalized OCRA Index method to classify risks under repetitive tasks conditions. Repetitive action tasks were performed in a controlled laboratory environment on ten healthy subjects, where optical and inertial sensors were used to capture movement. Body segment positions, displacements and joint angles were fed into the platform comparing their processing time and reliability. Although results indicate that optical systems have a better performance than inertial sensors for posture evaluation, the last has better practical applicability since optical markers occlusion in the working setup induced measurement errors. In addition, inertial systems are more likely to be used on in real working scenarios due to their ease of use and portability. Finally, inertial sensors combined with the digitized OCRA index method platform effectively reduces 67% of the needed evaluation time compared to traditional observational methods.
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