Abstract
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.
Highlights
Electromyographic (EMG) signals are biomedical signals that measure the electrical current generated during muscle contractions
The evolution of EMG signal analysis techniques combined with the development of new instrumentation has great potential in production engineering: fatigue monitoring of workers—based on live musculoskeletal risk assessment associated with an activity—or the development of new human–machine interaction systems, including remote control of robotic arms and other industrial equipment or the prediction of movements of workers, are feasible technologies
EMG applications in production engineering could be classified into three main groups: Ergonomics, Human–Machine interaction (HMI), and Monitoring
Summary
Electromyographic (EMG) signals are biomedical signals that measure the electrical current generated during muscle contractions. These signals represent neuromuscular activity and are dependent on the anatomical and physiological characteristics of the muscle. EMG has many applications, including the analysis of neuromusculoskeletal diseases, orthosis control, or ergonomic assessment. EMG technologies present some limitations that prevent their use beyond research and clinical environments. The evolution of EMG signal analysis techniques combined with the development of new instrumentation has great potential in production engineering: fatigue monitoring of workers—based on live musculoskeletal risk assessment associated with an activity—or the development of new human–machine interaction systems, including remote control of robotic arms and other industrial equipment or the prediction of movements of workers, are feasible technologies. The digital development of the industry, which is capable of generating and processing an enormous amount of data, will undoubtedly be benefited from techniques such as massive data analysis and artificial intelligence, which when applied to the analysis of biomedical signals will transform the human being into an active element of the production processes in an evolved and completely different way from what is known
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