Olmo Manuel Del, Domingo Rosario
Department of Construction and Manufacturing Engineering, Universidad Nacional de Educación a Distancia (UNED), C/Juan del Rosal 12, 28040 Madrid, Spain.
Materials (Basel). 2020 Dec 20;13(24):5815. doi: 10.3390/ma13245815.
Electromyography (EMG) signals are biomedical signals that measure electrical currents generated during muscle contraction. These signals are strongly influenced by physiological and anatomical characteristics of the muscles and represent the neuromuscular activities of the human body. The evolution of EMG analysis and acquisition techniques makes this technology more reliable for production engineering applications, overcoming some of its inherent issues. Taking as an example, the fatigue monitoring of workers as well as enriched human-machine interaction (HMI) systems used in collaborative tasks are now possible with this technology. The main objective of this research is to evaluate the current implementation of EMG technology within production engineering, its weaknesses, opportunities, and synergies with other technologies, with the aim of developing more natural and efficient HMI systems that could improve the safety and productivity within production environments.
肌电图（EMG）信号是一种生物医学信号，用于测量肌肉收缩过程中产生的电流。这些信号受到肌肉生理和解剖特征的强烈影响，代表了人体的神经肌肉活动。肌电图分析和采集技术的发展使这项技术在生产工程应用中更加可靠，克服了一些固有问题。例如，现在利用这项技术可以对工人进行疲劳监测，以及在协作任务中使用丰富的人机交互（HMI）系统。本研究的主要目的是评估肌电图技术在生产工程中的当前应用情况、其弱点、机会以及与其他技术的协同作用，旨在开发更自然、高效的人机交互系统，以提高生产环境中的安全性和生产率。
