Caporaso Teodorico, Grazioso Stanislao, Di Gironimo Giuseppe
Fraunhofer Joint Lab IDEAS, Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy.
Sensors (Basel). 2022 Mar 21;22(6):2413. doi: 10.3390/s22062413.
This work proposes a novel virtual reality system which makes use of wearable sensors for testing and validation of cooperative workplaces from the ergonomic point of view. The main objective is to show, in real time, the ergonomic evaluation based on a muscular activity analysis within the immersive virtual environment. The system comprises the following key elements: a robotic simulator for modeling the robot and the working environment; virtual reality devices for human immersion and interaction within the simulated environment; five surface electromyographic sensors; and one uniaxial accelerometer for measuring the human ergonomic status. The methodology comprises the following steps: firstly, the virtual environment is constructed with an associated immersive tutorial for the worker; secondly, an ergonomic toolbox is developed for muscular analysis. This analysis involves multiple ergonomic outputs: root mean square for each muscle, a global electromyographic score, and a synthetic index. They are all visualized in the immersive environment during the execution of the task. To test this methodology, experimental trials are conducted on a real use case in a human-robot cooperative workplace typical of the automotive industry. The results showed that the methodology can effectively be applied in the analysis of human-robot interaction, to endow the workers with self-awareness with respect to their physical conditions.
这项工作提出了一种新颖的虚拟现实系统，该系统利用可穿戴传感器从人体工程学角度对协作工作场所进行测试和验证。其主要目标是在沉浸式虚拟环境中实时展示基于肌肉活动分析的人体工程学评估。该系统包括以下关键要素：一个用于对机器人和工作环境进行建模的机器人模拟器；用于人类在模拟环境中沉浸和交互的虚拟现实设备；五个表面肌电传感器；以及一个用于测量人体工效学状态的单轴加速度计。该方法包括以下步骤：首先，构建虚拟环境并为工人配备相关的沉浸式教程；其次，开发一个用于肌肉分析的人体工程学工具箱。这种分析涉及多个人体工程学输出：每块肌肉的均方根、全局肌电评分和一个综合指数。在任务执行过程中，它们都在沉浸式环境中可视化。为了测试该方法，在汽车行业典型的人机协作工作场所的实际用例上进行了实验试验。结果表明，该方法可以有效地应用于人机交互分析，使工人对自己的身体状况有自我认知。
