Physical support systems such as exoskeletons are gaining importance to support workers in smart and connected factories by reducing physical strain. In order for the exoskeleton to be integrated seamlessly with humans and tasks within the work environment, it must be able to detect and adapt to human intentions. Compared to conventional control, myoelectric control, i.e., control based on measured muscle activity, enables improved human–robot interaction and more intuitive interaction with humans. This paper explores how myoelectric control can improve the interaction of industrial exoskeletons. For this purpose, the anatomical basics of electromyography (EMG) for detecting muscle activity are presented, followed by existing myoelectric control strategies. The insights gained are applied to the implementation of myoelectric control for industrial exoskeletons. It is shown that EMG-based control benefits from human adaptivity, making it particularly suitable in the case of variant movements and changing conditions. Even though using electromyographic control for adaptation of the exoskeleton includes efforts in terms of setup and calibration, the insights gained into the physiological state of the human (e.g., muscle activity, fatigue) are crucial for the adaptation to the user.


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    Title :

    Towards Myoelectric Control for Industrial Exoskeletons


    Contributors:

    Conference:

    MHI Colloquium ; 2024 ; Rostock, Germany September 24, 2024 - September 25, 2024



    Publication date :

    2025-03-20


    Size :

    12 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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