Université de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France.
Université de Lorraine, CNRS, CRAN, F-54000 Nancy, France.
Sensors (Basel). 2022 May 24;22(11):3981. doi: 10.3390/s22113981.
Improving the ergonomy of working environments is essential to reducing work-related musculo-skeletal disorders. We consider real-time ergonomic feedback a key technology for achieving such improvements. To this end, we present supportive tools for online evaluation and visualization of strenuous efforts and postures of a worker, also when physically interacting with a robot. A digital human model is used to estimate human kinematics and dynamics and visualize non-ergonomic joint angles, based on the on-line data acquired from a wearable motion tracking device.
改善工作环境的工效学对于减少与工作相关的肌肉骨骼疾病至关重要。我们认为实时工效学反馈是实现这一改进的关键技术。为此,我们提供了支持工具,用于在线评估和可视化工人的用力情况和姿势,即使在与机器人进行物理交互时也是如此。数字人体模型用于根据可穿戴运动跟踪设备在线获取的数据来估计人体运动学和动力学,并可视化非工效学关节角度。